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ORCIDOluwasanmi Koyejo
Sanmi Koyejo
Person information
- affiliation: University of Illinois at Urbana-Champaign, Department of Computer Science
- affiliation: Stanford University, Poldrack Lab
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2020 – today
- 2024
[c81]Sanmi Koyejo
, Bo Li:
Towards Trustworthy Large Language Models. WSDM 2024: 1126-1127- [i94]Minhao Jiang, Ken Ziyu Liu, Ming Zhong, Rylan Schaeffer, Siru Ouyang, Jiawei Han, Sanmi Koyejo:
Investigating Data Contamination for Pre-training Language Models. CoRR abs/2401.06059 (2024) - [i93]Zihao Wang, Chirag Nagpal, Jonathan Berant, Jacob Eisenstein, Alex D'Amour, Sanmi Koyejo, Victor Veitch:
Transforming and Combining Rewards for Aligning Large Language Models. CoRR abs/2402.00742 (2024) - [i92]Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo:
Scaling Laws for Downstream Task Performance of Large Language Models. CoRR abs/2402.04177 (2024) - [i91]Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Xiaojun Xu, Yuguang Yao, Hang Li, Kush R. Varshney, Mohit Bansal, Sanmi Koyejo, Yang Liu:
Rethinking Machine Unlearning for Large Language Models. CoRR abs/2402.08787 (2024) - [i90]Rylan Schaeffer, Nika Zahedi, Mikail Khona, Dhruv Pai, Sang T. Truong, Yilun Du, Mitchell Ostrow, Sarthak Chandra, Andres Carranza, Ila Rani Fiete, Andrey Gromov, Sanmi Koyejo:
Bridging Associative Memory and Probabilistic Modeling. CoRR abs/2402.10202 (2024) - [i89]Nathan Stromberg, Rohan Ayyagari, Monica Welfert, Sanmi Koyejo, Lalitha Sankar:
Robustness to Subpopulation Shift with Domain Label Noise via Regularized Annotation of Domains. CoRR abs/2402.11039 (2024) - [i88]Sang T. Truong, Duc Q. Nguyen, Toan Nguyen, Dong D. Le, Nhi N. Truong, Tho Quan, Sanmi Koyejo:
Crossing Linguistic Horizons: Finetuning and Comprehensive Evaluation of Vietnamese Large Language Models. CoRR abs/2403.02715 (2024) - [i87]Mercy Nyamewaa Asiedu, Awa Dieng, Iskandar Haykel, Negar Rostamzadeh, Stephen Pfohl, Chirag Nagpal, Maria Nagawa, Abigail Oppong, Sanmi Koyejo, Katherine A. Heller:
The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa. CoRR abs/2403.03357 (2024) - [i86]Katherine Tsai, Stephen R. Pfohl, Olawale Salaudeen, Nicole Chiou, Matt J. Kusner, Alexander D'Amour, Sanmi Koyejo, Arthur Gretton:
Proxy Methods for Domain Adaptation. CoRR abs/2403.07442 (2024) - 2023
- [c80]Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar:
One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning. AISTATS 2023: 1965-2001 - [c79]Zachary Robertson, Hantao Zhang, Sanmi Koyejo:
Cooperative Inverse Decision Theory for Uncertain Preferences. AISTATS 2023: 5854-5868 - [c78]Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai:
Adapting to Latent Subgroup Shifts via Concepts and Proxies. AISTATS 2023: 9637-9661 - [c77]Chulin Xie, Yunhui Long, Pin-Yu Chen, Qinbin Li, Sanmi Koyejo, Bo Li:
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks. CCS 2023: 1511-1525 - [c76]Boxiang Lyu, Zhe Feng, Zachary Robertson, Sanmi Koyejo:
Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions. ICML 2023: 23239-23263 - [c75]Rylan Schaeffer, Mikail Khona, Tzuhsuan Ma, Cristóbal Eyzaguirre, Sanmi Koyejo, Ila Fiete:
Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells. NeurIPS 2023 - [c74]Rylan Schaeffer, Brando Miranda, Sanmi Koyejo:
Are Emergent Abilities of Large Language Models a Mirage? NeurIPS 2023 - [c73]Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang, Chenhui Zhang, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li:
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models. NeurIPS 2023 - [c72]Pedro Cisneros-Velarde, Sanmi Koyejo:
Finite-sample guarantees for Nash Q-learning with linear function approximation. UAI 2023: 424-432 - [i85]Enyi Jiang, Yibo Jacky Zhang, Oluwasanmi Koyejo:
Federated Domain Adaptation via Gradient Projection. CoRR abs/2302.05049 (2023) - [i84]Pedro Cisneros-Velarde, Sanmi Koyejo:
Finite-sample Guarantees for Nash Q-learning with Linear Function Approximation. CoRR abs/2303.00177 (2023) - [i83]Rylan Schaeffer, Mikail Khona, Zachary Robertson, Akhilan Boopathy, Kateryna Pistunova, Jason W. Rocks, Ila Rani Fiete, Oluwasanmi Koyejo:
Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle. CoRR abs/2303.14151 (2023) - [i82]Mercy Nyamewaa Asiedu, Awa Dieng, Abigail Oppong, Maria Nagawa, Sanmi Koyejo, Katherine A. Heller:
Globalizing Fairness Attributes in Machine Learning: A Case Study on Health in Africa. CoRR abs/2304.02190 (2023) - [i81]Rylan Schaeffer, Brando Miranda, Sanmi Koyejo:
Are Emergent Abilities of Large Language Models a Mirage? CoRR abs/2304.15004 (2023) - [i80]Boxiang Lyu, Zhe Feng, Zachary Robertson, Sanmi Koyejo:
Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions. CoRR abs/2306.01799 (2023) - [i79]Zachary Robertson, Oluwasanmi Koyejo:
No Bidding, No Regret: Pairwise-Feedback Mechanisms for Digital Goods and Data Auctions. CoRR abs/2306.01860 (2023) - [i78]Zachary Robertson, Oluwasanmi Koyejo:
Layer-Wise Feedback Alignment is Conserved in Deep Neural Networks. CoRR abs/2306.01870 (2023) - [i77]Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang, Chenhui Zhang, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li:
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models. CoRR abs/2306.11698 (2023) - [i76]Berivan Isik, Francesco Pase, Deniz Gündüz, Sanmi Koyejo, Tsachy Weissman, Michele Zorzi:
Communication-Efficient Federated Learning through Importance Sampling. CoRR abs/2306.12625 (2023) - [i75]Alycia Lee, Brando Miranda, Sanmi Koyejo:
Beyond Scale: the Diversity Coefficient as a Data Quality Metric Demonstrates LLMs are Pre-trained on Formally Diverse Data. CoRR abs/2306.13840 (2023) - [i74]Brando Miranda, Patrick Yu, Saumya Goyal, Yu-Xiong Wang, Sanmi Koyejo:
Is Pre-training Truly Better Than Meta-Learning? CoRR abs/2306.13841 (2023) - [i73]Dhruv Pai, Andres Carranza, Rylan Schaeffer, Arnuv Tandon, Sanmi Koyejo:
FACADE: A Framework for Adversarial Circuit Anomaly Detection and Evaluation. CoRR abs/2307.10563 (2023) - [i72]Andres Carranza, Dhruv Pai, Rylan Schaeffer, Arnuv Tandon, Sanmi Koyejo:
Deceptive Alignment Monitoring. CoRR abs/2307.10569 (2023) - [i71]Rylan Schaeffer, Kateryna Pistunova, Samar Khanna, Sarthak Consul, Sanmi Koyejo:
Invalid Logic, Equivalent Gains: The Bizarreness of Reasoning in Language Model Prompting. CoRR abs/2307.10573 (2023) - [i70]Pablo Robles-Granda, Katherine Tsai, Oluwasanmi Koyejo:
Goodness-of-Fit of Attributed Probabilistic Graph Generative Models. CoRR abs/2308.03773 (2023) - [i69]Andy Zou, Long Phan, Sarah Chen, James Campbell, Phillip Guo, Richard Ren, Alexander Pan, Xuwang Yin, Mantas Mazeika, Ann-Kathrin Dombrowski, Shashwat Goel, Nathaniel Li, Michael J. Byun, Zifan Wang, Alex Mallen, Steven Basart, Sanmi Koyejo, Dawn Song, Matt Fredrikson, J. Zico Kolter, Dan Hendrycks:
Representation Engineering: A Top-Down Approach to AI Transparency. CoRR abs/2310.01405 (2023) - [i68]Yu Sun, Xinhao Li, Karan Dalal, Chloe Hsu, Sanmi Koyejo, Carlos Guestrin, Xiaolong Wang, Tatsunori Hashimoto, Xinlei Chen:
Learning to (Learn at Test Time). CoRR abs/2310.13807 (2023) - [i67]Rylan Schaeffer, Mikail Khona, Tzuhsuan Ma, Cristóbal Eyzaguirre, Sanmi Koyejo, Ila Rani Fiete:
Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells. CoRR abs/2311.02316 (2023) - [i66]Victor Lecomte, Kushal Thaman, Trevor Chow, Rylan Schaeffer, Sanmi Koyejo:
Incidental Polysemanticity. CoRR abs/2312.03096 (2023) - 2022
- [j14]Cong Xie, Oluwasanmi Koyejo, Indranil Gupta:
ZenoPS: A Distributed Learning System Integrating Communication Efficiency and Security. Algorithms 15(7): 233 (2022) - [j13]Katherine Tsai, Mladen Kolar, Oluwasanmi Koyejo:
A Nonconvex Framework for Structured Dynamic Covariance Recovery. J. Mach. Learn. Res. 23: 200:1-200:91 (2022) - [j12]Zengjie Song, Oluwasanmi Koyejo, Jiangshe Zhang:
Toward a Controllable Disentanglement Network. IEEE Trans. Cybern. 52(4): 2491-2504 (2022) - [c71]Peiye Zhuang, Liqian Ma, Sanmi Koyejo, Alexander G. Schwing:
Controllable Radiance Fields for Dynamic Face Synthesis. 3DV 2022: 1-11 - [c70]Nick Tucker, Bradley P. Sutton, Chase Duncan, Colin Lu, Sanmi Koyejo, Andrew J. Tsung, Jane Maksimovic, Tate Ralph, Sister M. Pieta, Matthew T. Bramlet:
Fully Automated Conversion Of Glioma Clinical MRI Scans Into A 3D Virtual Reality Model For Presurgical Planning. ANNSIM 2022: 392-403 - [c69]Xiaoyang Wang, Klara Nahrstedt, Oluwasanmi Koyejo:
Identifying Coarse-grained Independent Causal Mechanisms with Self-supervision. CLeaR 2022: 877-903 - [c68]Xiaojun Xu, Jacky Y. Zhang, Evelyn Ma, Hyun Ho Son, Sanmi Koyejo, Bo Li:
Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization. ICML 2022: 24770-24802 - [c67]Siddharth Biswal, Peiye Zhuang, Ayis Pyrros, Nasir Siddiqui, Sanmi Koyejo, Jimeng Sun:
EMIXER: End-to-end Multimodal X-ray Generation via Self-supervision. MLHC 2022: 297-324 - [c66]Yong Xie, Dakuo Wang, Pin-Yu Chen, Jinjun Xiong, Sijia Liu, Oluwasanmi Koyejo:
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction. NAACL-HLT 2022: 587-599 - [c65]Ibrahim M. Alabdulmohsin, Jessica Schrouff, Sanmi Koyejo:
A Reduction to Binary Approach for Debiasing Multiclass Datasets. NeurIPS 2022 - [c64]Jing Liu, Chulin Xie, Sanmi Koyejo, Bo Li:
CoPur: Certifiably Robust Collaborative Inference via Feature Purification. NeurIPS 2022 - [c63]Jessica Schrouff, Natalie Harris, Sanmi Koyejo, Ibrahim M. Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour:
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings. NeurIPS 2022 - [c62]Alexander Soen, Ibrahim M. Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie:
Fair Wrapping for Black-box Predictions. NeurIPS 2022 - [c61]Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo:
Quadratic metric elicitation for fairness and beyond. UAI 2022: 811-821 - [e1]Sanmi Koyejo, S. Mohamed, A. Agarwal, Danielle Belgrave, K. Cho, A. Oh:
Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022. 2022, ISBN 9781713871088 [contents] - [i65]Alexander Soen, Ibrahim Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie:
Fair Wrapping for Black-box Predictions. CoRR abs/2201.12947 (2022) - [i64]Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour:
Maintaining fairness across distribution shift: do we have viable solutions for real-world applications? CoRR abs/2202.01034 (2022) - [i63]Xiaojun Xu, Jacky Yibo Zhang, Evelyn Ma, Danny Son, Oluwasanmi Koyejo, Bo Li:
Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization. CoRR abs/2202.01832 (2022) - [i62]Yong Xie, Dakuo Wang, Pin-Yu Chen, Jinjun Xiong, Sijia Liu, Sanmi Koyejo:
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction. CoRR abs/2205.01094 (2022) - [i61]Ibrahim Alabdulmohsin, Jessica Schrouff, Oluwasanmi Koyejo:
A Reduction to Binary Approach for Debiasing Multiclass Datasets. CoRR abs/2205.15860 (2022) - [i60]Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar:
One Policy is Enough: Parallel Exploration with a Single Policy is Minimax Optimal for Reward-Free Reinforcement Learning. CoRR abs/2205.15891 (2022) - [i59]Brando Miranda, Patrick Yu, Yu-Xiong Wang, Sanmi Koyejo:
The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and Their Empirical Equivalence. CoRR abs/2208.01545 (2022) - [i58]Xiaoyang Wang, Dimitrios Dimitriadis, Sanmi Koyejo, Shruti Tople:
Invariant Aggregator for Defending Federated Backdoor Attacks. CoRR abs/2210.01834 (2022) - [i57]Peiye Zhuang, Liqian Ma, Oluwasanmi Koyejo, Alexander G. Schwing:
Controllable Radiance Fields for Dynamic Face Synthesis. CoRR abs/2210.05825 (2022) - [i56]Peiye Zhuang, Bliss Chapman, Ran Li, Oluwasanmi Koyejo:
Synthetic Power Analyses: Empirical Evaluation and Application to Cognitive Neuroimaging. CoRR abs/2210.05835 (2022) - [i55]Klara Nahrstedt, Naresh R. Shanbhag, Vikram S. Adve, Nancy M. Amato, Romit Roy Choudhury, Carl A. Gunter, Nam Sung Kim, Olgica Milenkovic, Sayan Mitra, Lav R. Varshney, Yurii Vlasov, Sarita V. Adve, Rashid Bashir, Andreas Cangellaris, James DiCarlo, Katie Driggs Campbell, Nick Feamster, Mattia Gazzola, Karrie Karahalios, Sanmi Koyejo, Paul G. Kwiat, Bo Li, Negar Mehr, Ravish Mehra, Andrew Miller, Daniela Rus, Alexander G. Schwing, Anshumali Shrivastava:
Coordinated Science Laboratory 70th Anniversary Symposium: The Future of Computing. CoRR abs/2210.08974 (2022) - [i54]Katherine Tsai, Boxin Zhao, Oluwasanmi Koyejo, Mladen Kolar:
Latent Multimodal Functional Graphical Model Estimation. CoRR abs/2210.17237 (2022) - [i53]Maohao Shen, Bowen Jiang, Jacky Yibo Zhang, Oluwasanmi Koyejo:
Batch Active Learning from the Perspective of Sparse Approximation. CoRR abs/2211.00246 (2022) - [i52]Safinah Ali, Sohini Upadhyay, Gaurush Hiranandani, Elena L. Glassman, Oluwasanmi Koyejo:
Metric Elicitation; Moving from Theory to Practice. CoRR abs/2212.03495 (2022) - [i51]Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai:
Adapting to Latent Subgroup Shifts via Concepts and Proxies. CoRR abs/2212.11254 (2022) - [i50]Olawale Salaudeen, Oluwasanmi Koyejo:
Target Conditioned Representation Independence (TCRI); From Domain-Invariant to Domain-General Representations. CoRR abs/2212.11342 (2022) - 2021
- [j11]James M. Shine, Mike Li, Oluwasanmi Koyejo, Ben D. Fulcher, Joseph T. Lizier:
Nonlinear reconfiguration of network edges, topology and information content during an artificial learning task. Brain Informatics 8(1): 26 (2021) - [j10]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - [c60]Jacky Zhang, Rajiv Khanna, Anastasios Kyrillidis, Sanmi Koyejo:
Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective. AISTATS 2021: 2782-2790 - [c59]Peiye Zhuang, Oluwasanmi Koyejo, Alexander G. Schwing:
Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation. ICLR 2021 - [c58]Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo:
Optimizing Black-box Metrics with Iterative Example Weighting. ICML 2021: 4239-4249 - [c57]Kaizhao Liang, Jacky Y. Zhang, Boxin Wang, Zhuolin Yang, Sanmi Koyejo, Bo Li:
Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability. ICML 2021: 6577-6587 - [c56]Patrick Cole, Ayis Pyrros, Oluwasanmi Koyejo:
Learning To Recover Sharp Detail From Simulated Low-Dose Ct Studies. ISBI 2021: 748-752 - [c55]Maohao Shen, Jacky Y. Zhang, Leihao Chen, Weiman Yan, Neel Jani, Brad Sutton, Oluwasanmi Koyejo:
Labeling Cost Sensitive Batch Active Learning For Brain Tumor Segmentation. ISBI 2021: 1269-1273 - [i49]Peiye Zhuang, Oluwasanmi Koyejo, Alexander G. Schwing:
Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation. CoRR abs/2102.01187 (2021) - [i48]Gaurush Hiranandani, Jatin Mathur, Oluwasanmi Koyejo, Mahdi Milani Fard, Harikrishna Narasimhan:
Optimizing Black-box Metrics with Iterative Example Weighting. CoRR abs/2102.09492 (2021) - [i47]Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu:
A Field Guide to Federated Optimization. CoRR abs/2107.06917 (2021) - [i46]Raj Kiriti Velicheti, Derek Xia, Oluwasanmi Koyejo:
Secure Byzantine-Robust Distributed Learning via Clustering. CoRR abs/2110.02940 (2021) - [i45]Katherine Tsai, Oluwasanmi Koyejo, Mladen Kolar:
Joint Gaussian Graphical Model Estimation: A Survey. CoRR abs/2110.10281 (2021) - [i44]Brando Miranda, Yu-Xiong Wang, Sanmi Koyejo:
Does MAML Only Work via Feature Re-use? A Data Centric Perspective. CoRR abs/2112.13137 (2021) - 2020
- [c54]Chase Duncan, Francis Roxas, Neel Jani, Jane Maksimovic, Matthew T. Bramlet, Brad Sutton, Sanmi Koyejo:
Some New Tricks for Deep Glioma Segmentation. BrainLes@MICCAI (2) 2020: 320-330 - [c53]Haroun Habeeb, Oluwasanmi Koyejo:
Towards a Deep Network Architecture for Structured Smoothness. ICLR 2020 - [c52]Gaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain:
Optimization and Analysis of the pAp@k Metric for Recommender Systems. ICML 2020: 4260-4270 - [c51]Cong Xie, Sanmi Koyejo, Indranil Gupta:
Zeno++: Robust Fully Asynchronous SGD. ICML 2020: 10495-10503 - [c50]Forest Yang, Sanmi Koyejo:
On the consistency of top-k surrogate losses. ICML 2020: 10727-10735 - [c49]Ran Liu, Cem Subakan, Aishwarya H. Balwani, Jennifer D. Whitesell, Julie Harris, Sanmi Koyejo, Eva L. Dyer:
A Generative Modeling Approach for Interpreting Population-Level Variability in Brain Structure. MICCAI (5) 2020: 257-266 - [c48]Gaurush Hiranandani, Harikrishna Narasimhan, Oluwasanmi Koyejo:
Fair Performance Metric Elicitation. NeurIPS 2020 - [c47]Cong Xie, Shuai Zheng, Oluwasanmi Koyejo, Indranil Gupta, Mu Li, Haibin Lin:
CSER: Communication-efficient SGD with Error Reset. NeurIPS 2020 - [c46]Forest Yang, Mouhamadou Cisse, Oluwasanmi Koyejo:
Fairness with Overlapping Groups; a Probabilistic Perspective. NeurIPS 2020 - [i43]Zengjie Song, Oluwasanmi Koyejo, Jiangshe Zhang:
Towards A Controllable Disentanglement Network. CoRR abs/2001.08572 (2020) - [i42]Amar Budhiraja, Gaurush Hiranandani, Navya Yarrabelly, Ayush Choure, Oluwasanmi Koyejo, Prateek Jain:
Rich-Item Recommendations for Rich-Users via GCNN: Exploiting Dynamic and Static Side Information. CoRR abs/2001.10495 (2020) - [i41]Gaurush Hiranandani, Harikrishna Narasimhan, Oluwasanmi Koyejo:
Fair Performance Metric Elicitation. CoRR abs/2006.12732 (2020) - [i40]Forest Yang, Moustapha Cissé, Sanmi Koyejo:
Fairness with Overlapping Groups. CoRR abs/2006.13485 (2020) - [i39]Kaizhao Liang, Jacky Y. Zhang, Oluwasanmi Koyejo, Bo Li:
Does Adversarial Transferability Indicate Knowledge Transferability? CoRR abs/2006.14512 (2020) - [i38]Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo:
Bayesian Coresets: An Optimization Perspective. CoRR abs/2007.00715 (2020) - [i37]Siddharth Biswal, Peiye Zhuang, Ayis Pyrros, Nasir Siddiqui, Sanmi Koyejo, Jimeng Sun:
EMIXER: End-to-end Multimodal X-ray Generation via Self-supervision. CoRR abs/2007.05597 (2020) - [i36]Cong Xie, Shuai Zheng, Oluwasanmi Koyejo, Indranil Gupta, Mu Li, Haibin Lin:
CSER: Communication-efficient SGD with Error Reset. CoRR abs/2007.13221 (2020) - [i35]Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo:
Quadratic Metric Elicitation with Application to Fairness. CoRR abs/2011.01516 (2020) - [i34]Katherine Tsai, Mladen Kolar, Oluwasanmi Koyejo:
A Nonconvex Framework for Structured Dynamic Covariance Recovery. CoRR abs/2011.05601 (2020)
2010 – 2019
- 2019
- [j9]Anqi Wu, Oluwasanmi Koyejo, Jonathan W. Pillow:
Dependent relevance determination for smooth and structured sparse regression. J. Mach. Learn. Res. 20: 89:1-89:43 (2019) - [c45]Peiye Zhuang, Bliss Chapman, Ran Li, Sanmi Koyejo:
Synthetic Power Analyses: Empirical Evaluation and Application to Cognitive Neuroimaging. ACSSC 2019: 1192-1196 - [c44]Gaurush Hiranandani, Shant Boodaghians, Ruta Mehta, Oluwasanmi Koyejo:
Performance Metric Elicitation from Pairwise Classifier Comparisons. AISTATS 2019: 371-379 - [c43]Rajiv Khanna, Been Kim, Joydeep Ghosh, Sanmi Koyejo:
Interpreting Black Box Predictions using Fisher Kernels. AISTATS 2019: 3382-3390 - [c42]Ishan Deshpande, Yuan-Ting Hu, Ruoyu Sun, Ayis Pyrros, Nasir Siddiqui, Sanmi Koyejo, Zhizhen Zhao, David A. Forsyth, Alexander G. Schwing:
Max-Sliced Wasserstein Distance and Its Use for GANs. CVPR 2019: 10648-10656 - [c41]Sinong Geng, Minhao Yan, Mladen Kolar, Sanmi Koyejo:
Partially Linear Additive Gaussian Graphical Models. ICML 2019: 2180-2190 - [c40]Cong Xie, Sanmi Koyejo, Indranil Gupta:
Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance. ICML 2019: 6893-6901 - [c39]Peiye Zhuang, Alexander G. Schwing, Oluwasanmi Koyejo:
FMRI Data Augmentation Via Synthesis. ISBI 2019: 1783-1787 - [c38]Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo:
Learning Sparse Distributions using Iterative Hard Thresholding. NeurIPS 2019: 6757-6766 - [c37]Gaurush Hiranandani, Shant Boodaghians, Ruta Mehta, Oluwasanmi Koyejo:
Multiclass Performance Metric Elicitation. NeurIPS 2019: 9351-9360 - [c36]Cong Xie, Oluwasanmi Koyejo, Indranil Gupta:
SLSGD: Secure and Efficient Distributed On-device Machine Learning. ECML/PKDD (2) 2019: 213-228 - [c35]Cong Xie, Oluwasanmi Koyejo, Indranil Gupta:
Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation. UAI 2019: 261-270 - [c34]Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo:
Joint Nonparametric Precision Matrix Estimation with Confounding. UAI 2019: 378-388 - [c33]Gaurush Hiranandani, Raghav Somani, Oluwasanmi Koyejo, Sreangsu Acharyya:
Clustered Monotone Transforms for Rating Factorization. WSDM 2019: 132-140 - [i33]Forest Yang, Sanmi Koyejo:
On the Consistency of Top-k Surrogate Losses. CoRR abs/1901.11141 (2019) - [i32]Cong Xie, Sanmi Koyejo, Indranil Gupta:
Asynchronous Federated Optimization. CoRR abs/1903.03934 (2019) - [i31]Cong Xie, Sanmi Koyejo, Indranil Gupta:
Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation. CoRR abs/1903.03936 (2019) - [i30]Cong Xie, Sanmi Koyejo, Indranil Gupta:
Practical Distributed Learning: Secure Machine Learning with Communication-Efficient Local Updates. CoRR abs/1903.06996 (2019) - [i29]Ishan Deshpande, Yuan-Ting Hu, Ruoyu Sun, Ayis Pyrros, Nasir Siddiqui, Sanmi Koyejo, Zhizhen Zhao, David A. Forsyth, Alexander G. Schwing:
Max-Sliced Wasserstein Distance and its use for GANs. CoRR abs/1904.05877 (2019) - [i28]Sinong Geng, Minhao Yan, Mladen Kolar, Oluwasanmi Koyejo:
Partially Linear Additive Gaussian Graphical Models. CoRR abs/1906.03362 (2019) - [i27]Peiye Zhuang, Alexander G. Schwing, Sanmi Koyejo:
FMRI data augmentation via synthesis. CoRR abs/1907.06134 (2019) - [i26]Shalmali Joshi, Oluwasanmi Koyejo, Warut Vijitbenjaronk, Been Kim, Joydeep Ghosh:
Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems. CoRR abs/1907.09615 (2019) - [i25]Xiaoyan Wang, Ran Li, Bowei Yan, Oluwasanmi Koyejo:
Consistent Classification with Generalized Metrics. CoRR abs/1908.09057 (2019) - [i24]Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo:
Learning Sparse Distributions using Iterative Hard Thresholding. CoRR abs/1910.13389 (2019) - [i23]Cong Xie, Oluwasanmi Koyejo, Indranil Gupta, Haibin Lin:
Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates. CoRR abs/1911.09030 (2019) - [i22]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. CoRR abs/1912.04977 (2019) - [i21]Zengjie Song, Oluwasanmi Koyejo, Jiangshe Zhang:
Learning Controllable Disentangled Representations with Decorrelation Regularization. CoRR abs/1912.11675 (2019) - 2018
- [c32]Michael Riis Andersen, Ole Winther, Lars Kai Hansen, Russell A. Poldrack, Oluwasanmi Koyejo:
Bayesian Structure Learning for Dynamic Brain Connectivity. AISTATS 2018: 1436-1446 - [c31]Bowei Yan, Oluwasanmi Koyejo, Kai Zhong, Pradeep Ravikumar:
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics. ICML 2018: 5527-5536 - [c30]Yizhi Zhu, Oluwasanmi Koyejo:
Clustered Fused Graphical Lasso. UAI 2018: 487-496 - [i20]Cong Xie, Oluwasanmi Koyejo, Indranil Gupta:
Generalized Byzantine-tolerant SGD. CoRR abs/1802.10116 (2018) - [i19]Y. Cem Sübakan, Oluwasanmi Koyejo, Paris Smaragdis:
Learning the Base Distribution in Implicit Generative Models. CoRR abs/1803.04357 (2018) - [i18]Cong Xie, Oluwasanmi Koyejo, Indranil Gupta:
Phocas: dimensional Byzantine-resilient stochastic gradient descent. CoRR abs/1805.09682 (2018) - [i17]Cong Xie, Oluwasanmi Koyejo, Indranil Gupta:
Zeno: Byzantine-suspicious stochastic gradient descent. CoRR abs/1805.10032 (2018) - [i16]Bowei Yan, Oluwasanmi Koyejo, Kai Zhong, Pradeep Ravikumar:
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics. CoRR abs/1806.00640 (2018) - [i15]Gaurush Hiranandani, Shant Boodaghians, Ruta Mehta, Oluwasanmi Koyejo:
Eliciting Binary Performance Metrics. CoRR abs/1806.01827 (2018) - [i14]Shalmali Joshi, Oluwasanmi Koyejo, Been Kim, Joydeep Ghosh:
xGEMs: Generating Examplars to Explain Black-Box Models. CoRR abs/1806.08867 (2018) - [i13]Yogatheesan Varatharajah, Brent M. Berry, Sanmi Koyejo, Ravishankar K. Iyer:
A Contextual-bandit-based Approach for Informed Decision-making in Clinical Trials. CoRR abs/1809.00258 (2018) - [i12]Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo:
Joint Nonparametric Precision Matrix Estimation with Confounding. CoRR abs/1810.07147 (2018) - [i11]Rajiv Khanna, Been Kim, Joydeep Ghosh, Oluwasanmi Koyejo:
Interpreting Black Box Predictions using Fisher Kernels. CoRR abs/1810.10118 (2018) - [i10]Gaurush Hiranandani, Raghav Somani, Oluwasanmi Koyejo, Sreangsu Acharyya:
Clustered Monotone Transforms for Rating Factorization. CoRR abs/1811.00159 (2018) - 2017
- [j8]Ro'ee Gilron, Jonathan D. Rosenblatt, Oluwasanmi Koyejo, Russell A. Poldrack, Roy Mukamel:
What's in a pattern? Examining the type of signal multivariate analysis uncovers at the group level. NeuroImage 146: 113-120 (2017) - [j7]Timothy N. Rubin, Oluwasanmi Koyejo, Krzysztof J. Gorgolewski, Michael N. Jones, Russell A. Poldrack, Tal Yarkoni:
Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition. PLoS Comput. Biol. 13(10) (2017) - [c29]Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo:
Frequency Domain Predictive Modelling with Aggregated Data. AISTATS 2017: 971-980 - [c28]Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack, Oluwasanmi Koyejo:
Information Projection and Approximate Inference for Structured Sparse Variables. AISTATS 2017: 1358-1366 - [c27]Krzysztof Dembczynski, Wojciech Kotlowski, Oluwasanmi Koyejo, Nagarajan Natarajan:
Consistency Analysis for Binary Classification Revisited. ICML 2017: 961-969 - [c26]Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack, Oluwasanmi Koyejo:
A Deflation Method for Structured Probabilistic PCA. SDM 2017: 534-542 - 2016
- [j6]Shalmali Joshi, Joydeep Ghosh, Mark Reid, Oluwasanmi Koyejo:
Rényi divergence minimization based co-regularized multiview clustering. Mach. Learn. 104(2-3): 411-439 (2016) - [c25]Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo:
Sparse Parameter Recovery from Aggregated Data. ICML 2016: 1090-1099 - [c24]Megasthenis Asteris, Anastasios Kyrillidis, Oluwasanmi Koyejo, Russell A. Poldrack:
A Simple and Provable Algorithm for Sparse Diagonal CCA. ICML 2016: 1148-1157 - [c23]Nagarajan Natarajan, Oluwasanmi Koyejo, Pradeep Ravikumar, Inderjit S. Dhillon:
Optimal Classification with Multivariate Losses. ICML 2016: 1530-1538 - [c22]Timothy N. Rubin, Oluwasanmi Koyejo, Michael N. Jones, Tal Yarkoni:
Generalized Correspondence-LDA Models (GC-LDA) for Identifying Functional Regions in the Brain. NIPS 2016: 1118-1126 - [c21]Suriya Gunasekar, Oluwasanmi Koyejo, Joydeep Ghosh:
Preference Completion from Partial Rankings. NIPS 2016: 1370-1378 - [c20]Been Kim, Oluwasanmi Koyejo, Rajiv Khanna:
Examples are not enough, learn to criticize! Criticism for Interpretability. NIPS 2016: 2280-2288 - [i9]Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo:
Generalized Linear Models for Aggregated Data. CoRR abs/1605.04466 (2016) - [i8]Megasthenis Asteris, Anastasios Kyrillidis, Oluwasanmi Koyejo, Russell A. Poldrack:
A simple and provable algorithm for sparse diagonal CCA. CoRR abs/1605.08961 (2016) - [i7]Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack, Oluwasanmi Koyejo:
Information Projection and Approximate Inference for Structured Sparse Variables. CoRR abs/1607.03204 (2016) - [i6]Suriya Gunasekar, Oluwasanmi Koyejo, Joydeep Ghosh:
Preference Completion from Partial Rankings. CoRR abs/1611.04218 (2016) - 2015
- [j5]James M. Shine, Oluwasanmi Koyejo, Peter T. Bell, Krzysztof J. Gorgolewski, Moran Gilat, Russell A. Poldrack:
Estimation of dynamic functional connectivity using Multiplication of Temporal Derivatives. NeuroImage 122: 399-407 (2015) - [c19]Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo:
Generalized Linear Models for Aggregated Data. AISTATS 2015 - [c18]Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack, Oluwasanmi Koyejo:
Sparse Submodular Probabilistic PCA. AISTATS 2015 - [c17]Shalmali Joshi, Oluwasanmi Koyejo, Kristine Resurreccion, Joydeep Ghosh:
Simultaneous Prognosis and Exploratory Analysis of Multiple Chronic Conditions Using Clinical Notes. ICHI 2015: 243-252 - [c16]Shalmali Joshi, Oluwasanmi Koyejo, Joydeep Ghosh:
Simultaneous Prognosis of Multiple Chronic Conditions from Heterogeneous EHR Data. ICHI 2015: 497 - [c15]Oluwasanmi Koyejo, Nagarajan Natarajan, Pradeep Ravikumar, Inderjit S. Dhillon:
Consistent Multilabel Classification. NIPS 2015: 3321-3329 - [i5]Nagarajan Natarajan, Oluwasanmi Koyejo, Pradeep Ravikumar, Inderjit S. Dhillon:
Optimal Decision-Theoretic Classification Using Non-Decomposable Performance Metrics. CoRR abs/1505.01802 (2015) - 2014
- [j4]Oluwasanmi Koyejo, Cheng H. Lee, Joydeep Ghosh:
A constrained matrix-variate Gaussian process for transposable data. Mach. Learn. 97(1-2): 103-127 (2014) - [c14]Oluwasanmi Koyejo, Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack:
On Prior Distributions and Approximate Inference for Structured Variables. NIPS 2014: 676-684 - [c13]Anqi Wu, Mijung Park, Oluwasanmi Koyejo, Jonathan W. Pillow:
Sparse Bayesian structure learning with dependent relevance determination priors. NIPS 2014: 1628-1636 - [c12]Oluwasanmi Koyejo, Nagarajan Natarajan, Pradeep Ravikumar, Inderjit S. Dhillon:
Consistent Binary Classification with Generalized Performance Metrics. NIPS 2014: 2744-2752 - [i4]Oluwasanmi Koyejo, Cheng H. Lee, Joydeep Ghosh:
A Constrained Matrix-Variate Gaussian Process for Transposable Data. CoRR abs/1404.6702 (2014) - 2013
- [j3]Russell A. Poldrack, Deanna M. Barch, Jason P. Mitchell, Tor D. Wager, Anthony D. Wagner, Joseph T. Devlin, Chad Cumba, Oluwasanmi Koyejo, Michael P. Milham:
Toward open sharing of task-based fMRI data: the OpenfMRI project. Frontiers Neuroinformatics 7: 12 (2013) - [c11]Mijung Park, Oluwasanmi Koyejo, Joydeep Ghosh, Russell A. Poldrack, Jonathan W. Pillow:
Bayesian Structure Learning for Functional Neuroimaging. AISTATS 2013: 489-497 - [c10]Cheng H. Lee, Oluwasanmi Koyejo, Joydeep Ghosh:
Identifying candidate disease genes using a trace norm constrained bipartite raking model. EMBC 2013: 3459-3462 - [c9]Oluwasanmi Koyejo, Cheng H. Lee, Joydeep Ghosh:
Constrained Gaussian Process Regression for Gene-Disease Association. ICDM Workshops 2013: 72-79 - [c8]Oluwasanmi Koyejo, Priyank Patel, Joydeep Ghosh, Russell A. Poldrack:
Learning Predictive Cognitive Structure from fMRI Using Supervised Topic Models. PRNI 2013: 9-12 - [c7]Oluwasanmi Koyejo, Sreangsu Acharyya, Joydeep Ghosh:
Retargeted matrix factorization for collaborative filtering. RecSys 2013: 49-56 - [c6]Oluwasanmi Koyejo, Joydeep Ghosh:
Constrained Bayesian Inference for Low Rank Multitask Learning. UAI 2013 - [i3]Oluwasanmi Koyejo, Cheng H. Lee, Joydeep Ghosh:
The trace norm constrained matrix-variate Gaussian process for multitask bipartite ranking. CoRR abs/1302.2576 (2013) - [i2]Oluwasanmi Koyejo, Joydeep Ghosh:
Constrained Bayesian Inference for Low Rank Multitask Learning. CoRR abs/1309.6840 (2013) - 2012
- [c5]Sreangsu Acharyya, Oluwasanmi Koyejo, Joydeep Ghosh:
Learning to Rank With Bregman Divergences and Monotone Retargeting. UAI 2012: 15-25 - [i1]Sreangsu Acharyya, Oluwasanmi Koyejo, Joydeep Ghosh:
Learning to Rank With Bregman Divergences and Monotone Retargeting. CoRR abs/1210.4851 (2012) - 2011
- [j2]Roger Azevedo, Gautam Biswas, Dan Bohus, Ted Carmichael, Mark A. Finlayson, Mirsad Hadzikadic, Catherine Havasi, Eric Horvitz, Takayuki Kanda, Oluwasanmi Koyejo, William F. Lawless, Douglas B. Lenat, Felipe Meneguzzi, Bilge Mutlu, Jean Oh, Roberto Pirrone, Antoine Raux, Donald A. Sofge, Gita Sukthankar, Benjamin Van Durme:
Reports of the AAAI 2010 Fall Symposia. AI Mag. 32(1): 93-100 (2011) - [c4]Oluwasanmi Koyejo, Joydeep Ghosh:
A kernel-based approach to exploiting interaction-networks in heterogeneous information sources for improved recommender systems. HetRec@RecSys 2011: 9-16 - 2010
- [j1]Roger Azevedo, Trevor J. M. Bench-Capon, Gautam Biswas, Ted Carmichael, Nancy L. Green, Mirsad Hadzikadic, Oluwasanmi Koyejo, Unmesh Kurup, Simon Parsons, Roberto Pirrone, Henry Prakken, Alexei V. Samsonovich, Donia Scott, Richard Souvenir:
Reports of the AAAI 2009 Fall Symposia. AI Mag. 31(1): 88-94 (2010) - [c3]Oluwasanmi Koyejo, Richard Souvenir:
Organizing Committee. AAAI Fall Symposium: Manifold Learning and Its Applications 2010 - [c2]Oluwasanmi Koyejo, Richard Souvenir:
Preface: Manifold Learning and Its Applications. AAAI Fall Symposium: Manifold Learning and Its Applications 2010
2000 – 2009
- 2009
- [c1]Oluwasanmi Koyejo, Joydeep Ghosh:
MiPPS: A Generative Model for Multi-Manifold Clustering. AAAI Fall Symposium: Manifold Learning and Its Applications 2009
Coauthor Index
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