Kush Bhatia - RankMe

50 papers A* 15A 4Journal 27Unranked 3

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Automated Rewards via LLM-Generated Progress Functions. CoRR Vishnu Sarukkai, Brennan Shacklett, Zander Majercik, Kush Bhatia, Christopher Ré, Kayvon Fatahalian
2024	J	`jnl`	Cookbook: A framework for improving LLM generative abilities via programmatic data generating templates. CoRR Avanika Narayan, Mayee F. Chen, Kush Bhatia, Christopher Ré
2024	A*	`conf`	The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry. ICLR Michael Zhang, Kush Bhatia, Hermann Kumbong, Christopher Ré
2024	J	`jnl`	The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry. CoRR Michael Zhang, Kush Bhatia, Hermann Kumbong, Christopher Ré
2023	A*	`conf`	A case for reframing automated medical image classification as segmentation. NeurIPS Sarah M. Hooper, Mayee F. Chen, Khaled Saab, Kush Bhatia, Curtis P. Langlotz, Christopher Ré
2023	A*	`conf`	Ask Me Anything: A simple strategy for prompting language models. ICLR Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel J. Orr, Neel Guha, Kush Bhatia, Ines Chami, Christopher Ré
2023	J	`jnl`	Congested Bandits: Optimal Routing via Short-term Resets. CoRR Pranjal Awasthi, Kush Bhatia, Sreenivas Gollapudi, Kostas Kollias
2023	A*	`conf`	Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification. NeurIPS Neel Guha, Mayee F. Chen, Kush Bhatia, Azalia Mirhoseini, Frederic Sala, Christopher Ré
2023	J	`jnl`	Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification. CoRR Neel Guha, Mayee F. Chen, Kush Bhatia, Azalia Mirhoseini, Frederic Sala, Christopher Ré
2023	A*	`conf`	On the Sensitivity of Reward Inference to Misspecified Human Models. ICLR Joey Hong, Kush Bhatia, Anca D. Dragan
2023	A	`conf`	Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws. AISTATS Kush Bhatia, Wenshuo Guo, Jacob Steinhardt
2023	J	`jnl`	Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws. CoRR Kush Bhatia, Wenshuo Guo, Jacob Steinhardt
2023	J	`jnl`	Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models. CoRR Mayee F. Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré
2023	A*	`conf`	Skill-it! A data-driven skills framework for understanding and training language models. NeurIPS Mayee F. Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré
2023	J	`jnl`	SuperHF: Supervised Iterative Learning from Human Feedback. CoRR Gabriel Mukobi, Peter Chatain, Su Fong, Robert Windesheim, Gitta Kutyniok, Kush Bhatia, Silas Alberti
2023	A*	`conf`	TART: A plug-and-play Transformer module for task-agnostic reasoning. NeurIPS Kush Bhatia, Avanika Narayan, Christopher De Sa, Christopher Ré
2023	J	`jnl`	TART: A plug-and-play Transformer module for task-agnostic reasoning. CoRR Kush Bhatia, Avanika Narayan, Christopher De Sa, Christopher Ré
2022	J	`jnl`	Ask Me Anything: A simple strategy for prompting language models. CoRR Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel J. Orr, Neel Guha, Kush Bhatia, Ines Chami, Frederic Sala, Christopher Ré
2022	A*	`conf`	Congested Bandits: Optimal Routing via Short-term Resets. ICML Pranjal Awasthi, Kush Bhatia, Sreenivas Gollapudi, Kostas Kollias
2022	—	`—`	Learning when Objectives are Hard to Specify Kush Bhatia
2022	J	`jnl`	On the Sensitivity of Reward Inference to Misspecified Human Models. CoRR Joey Hong, Kush Bhatia, Anca D. Dragan
2022	J	`jnl`	Statistical and Computational Trade-offs in Variational Inference: A Case Study in Inferential Model Selection. CoRR Kush Bhatia, Nikki Lijing Kuang, Yi-An Ma, Yixin Wang
2022	A*	`conf`	The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models. ICLR Alexander Pan, Kush Bhatia, Jacob Steinhardt
2022	J	`jnl`	The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models. CoRR Alexander Pan, Kush Bhatia, Jacob Steinhardt
2021	A	`conf`	Agnostic Learning with Unknown Utilities. ITCS Kush Bhatia, Peter L. Bartlett, Anca D. Dragan, Jacob Steinhardt
2021	J	`jnl`	Agnostic learning with unknown utilities. CoRR Kush Bhatia, Peter L. Bartlett, Anca D. Dragan, Jacob Steinhardt
2021	J	`jnl`	Preference learning along multiple criteria: A game-theoretic perspective. CoRR Kush Bhatia, Ashwin Pananjady, Peter L. Bartlett, Anca D. Dragan, Martin J. Wainwright
2020	J	`jnl`	Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems. J. Mach. Learn. Res. Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L. Bartlett, Martin J. Wainwright
2020	A*	`conf`	Online learning with dynamics: A minimax perspective. NeurIPS Kush Bhatia, Karthik Sridharan
2020	J	`jnl`	Online learning with dynamics: A minimax perspective. CoRR Kush Bhatia, Karthik Sridharan
2020	A*	`conf`	Preference learning along multiple criteria: A game-theoretic perspective. NeurIPS Kush Bhatia, Ashwin Pananjady, Peter L. Bartlett, Anca D. Dragan, Martin J. Wainwright
2019	A*	`conf`	Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression. COLT Arun Sai Suggala, Kush Bhatia, Pradeep Ravikumar, Prateek Jain
2019	J	`jnl`	Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression. CoRR Arun Sai Suggala, Kush Bhatia, Pradeep Ravikumar, Prateek Jain
2019	J	`jnl`	Bayesian Robustness: A Nonasymptotic Viewpoint. CoRR Kush Bhatia, Yi-An Ma, Anca D. Dragan, Peter L. Bartlett, Michael I. Jordan
2019	A	`conf`	Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems. AISTATS Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L. Bartlett, Martin J. Wainwright
2019	J	`jnl`	FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network. CoRR Aditya Kusupati, Manish Singh, Kush Bhatia, Ashish Kumar, Prateek Jain, Manik Varma
2019	A*	`conf`	POLITEX: Regret Bounds for Policy Iteration using Expert Prediction. ICML Yasin Abbasi-Yadkori, Peter L. Bartlett, Kush Bhatia, Nevena Lazic, Csaba Szepesvári, Gellért Weisz
2018	J	`jnl`	Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems. CoRR Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L. Bartlett, Martin J. Wainwright
2018	A	`conf`	Establishing Appropriate Trust via Critical States. IROS Sandy H. Huang, Kush Bhatia, Pieter Abbeel, Anca D. Dragan
2018	J	`jnl`	Establishing Appropriate Trust via Critical States. CoRR Sandy H. Huang, Kush Bhatia, Pieter Abbeel, Anca D. Dragan
2018	A*	`conf`	FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network. NeurIPS Aditya Kusupati, Manish Singh, Kush Bhatia, Ashish Kumar, Prateek Jain, Manik Varma
2018	J	`jnl`	Gen-Oja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation. CoRR Kush Bhatia, Aldo Pacchiano, Nicolas Flammarion, Peter L. Bartlett, Michael I. Jordan
2018	A*	`conf`	Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation. NeurIPS Kush Bhatia, Aldo Pacchiano, Nicolas Flammarion, Peter L. Bartlett, Michael I. Jordan
2017	—	`conf`	Consistent Robust Regression. NIPS Kush Bhatia, Prateek Jain, Parameswaran Kamalaruban, Purushottam Kar
2016	J	`jnl`	Efficient and Consistent Robust Time Series Analysis. CoRR Kush Bhatia, Prateek Jain, Parameswaran Kamalaruban, Purushottam Kar
2016	J	`jnl`	Lazy Generic Cuts. Comput. Vis. Image Underst. Dinesh Khandelwal, Kush Bhatia, Chetan Arora, Parag Singla
2015	J	`jnl`	Locally Non-linear Embeddings for Extreme Multi-label Learning. CoRR Kush Bhatia, Himanshu Jain, Purushottam Kar, Prateek Jain, Manik Varma
2015	—	`conf`	Robust Regression via Hard Thresholding. NIPS Kush Bhatia, Prateek Jain, Purushottam Kar
2015	J	`jnl`	Robust Regression via Hard Thresholding. CoRR Kush Bhatia, Prateek Jain, Purushottam Kar
2015	—	`conf`	Sparse Local Embeddings for Extreme Multi-label Classification. NIPS Kush Bhatia, Himanshu Jain, Purushottam Kar, Manik Varma, Prateek Jain