Kush Bhatia

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 42

Top Topics

Hard Thresholding

Top Venues

Publications

Michael Zhang, Kush Bhatia, Hermann Kumbong, Christopher Ré
The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry. ICLR (2024)
Michael Zhang, Kush Bhatia, Hermann Kumbong, Christopher Ré
The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry. CoRR (2024)
Joey Hong, Kush Bhatia, Anca D. Dragan
On the Sensitivity of Reward Inference to Misspecified Human Models. ICLR (2023)
Pranjal Awasthi, Kush Bhatia, Sreenivas Gollapudi, Kostas Kollias
Congested Bandits: Optimal Routing via Short-term Resets. CoRR (2023)
Neel Guha, Mayee F. Chen, Kush Bhatia, Azalia Mirhoseini, Frederic Sala, Christopher Ré
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification. NeurIPS (2023)
Gabriel Mukobi, Peter Chatain, Su Fong, Robert Windesheim, Gitta Kutyniok, Kush Bhatia, Silas Alberti
SuperHF: Supervised Iterative Learning from Human Feedback. CoRR (2023)
Kush Bhatia, Avanika Narayan, Christopher De Sa, Christopher Ré
TART: A plug-and-play Transformer module for task-agnostic reasoning. CoRR (2023)
Neel Guha, Mayee F. Chen, Kush Bhatia, Azalia Mirhoseini, Frederic Sala, Christopher Ré
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification. CoRR (2023)
Mayee F. Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré
Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models. CoRR (2023)
Mayee F. Chen, Nicholas Roberts, Kush Bhatia, Jue Wang, Ce Zhang, Frederic Sala, Christopher Ré
Skill-it! A data-driven skills framework for understanding and training language models. NeurIPS (2023)
Kush Bhatia, Avanika Narayan, Christopher De Sa, Christopher Ré
TART: A plug-and-play Transformer module for task-agnostic reasoning. NeurIPS (2023)
Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel J. Orr, Neel Guha, Kush Bhatia, Ines Chami, Christopher Ré
Ask Me Anything: A simple strategy for prompting language models. ICLR (2023)
Kush Bhatia, Wenshuo Guo, Jacob Steinhardt
Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws. AISTATS (2023)
Sarah M. Hooper, Mayee F. Chen, Khaled Saab, Kush Bhatia, Curtis P. Langlotz, Christopher Ré
A case for reframing automated medical image classification as segmentation. NeurIPS (2023)
Kush Bhatia, Wenshuo Guo, Jacob Steinhardt
Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws. CoRR (2023)
Alexander Pan, Kush Bhatia, Jacob Steinhardt
The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models. ICLR (2022)
Alexander Pan, Kush Bhatia, Jacob Steinhardt
The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models. CoRR (2022)
Simran Arora, Avanika Narayan, Mayee F. Chen, Laurel J. Orr, Neel Guha, Kush Bhatia, Ines Chami, Frederic Sala, Christopher Ré
Ask Me Anything: A simple strategy for prompting language models. CoRR (2022)
Pranjal Awasthi, Kush Bhatia, Sreenivas Gollapudi, Kostas Kollias
Congested Bandits: Optimal Routing via Short-term Resets. ICML (2022)
Joey Hong, Kush Bhatia, Anca D. Dragan
On the Sensitivity of Reward Inference to Misspecified Human Models. CoRR (2022)
Kush Bhatia, Nikki Lijing Kuang, Yi-An Ma, Yixin Wang
Statistical and Computational Trade-offs in Variational Inference: A Case Study in Inferential Model Selection. CoRR (2022)
Kush Bhatia, Ashwin Pananjady, Peter L. Bartlett, Anca D. Dragan, Martin J. Wainwright
Preference learning along multiple criteria: A game-theoretic perspective. CoRR (2021)
Kush Bhatia, Peter L. Bartlett, Anca D. Dragan, Jacob Steinhardt
Agnostic learning with unknown utilities. CoRR (2021)
Kush Bhatia, Peter L. Bartlett, Anca D. Dragan, Jacob Steinhardt
Agnostic Learning with Unknown Utilities. ITCS (2021)
Kush Bhatia, Ashwin Pananjady, Peter L. Bartlett, Anca D. Dragan, Martin J. Wainwright
Preference learning along multiple criteria: A game-theoretic perspective. NeurIPS (2020)
Kush Bhatia, Karthik Sridharan
Online learning with dynamics: A minimax perspective. NeurIPS (2020)
Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L. Bartlett, Martin J. Wainwright
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems. J. Mach. Learn. Res. 21 (2020)
Kush Bhatia, Karthik Sridharan
Online learning with dynamics: A minimax perspective. CoRR (2020)
Arun Sai Suggala, Kush Bhatia, Pradeep Ravikumar, Prateek Jain
Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression. COLT (2019)
Aditya Kusupati, Manish Singh, Kush Bhatia, Ashish Kumar, Prateek Jain, Manik Varma
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network. CoRR (2019)
Kush Bhatia, Yi-An Ma, Anca D. Dragan, Peter L. Bartlett, Michael I. Jordan
Bayesian Robustness: A Nonasymptotic Viewpoint. CoRR (2019)
Arun Sai Suggala, Kush Bhatia, Pradeep Ravikumar, Prateek Jain
Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression. CoRR (2019)
Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L. Bartlett, Martin J. Wainwright
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems. AISTATS (2019)
Sandy H. Huang, Kush Bhatia, Pieter Abbeel, Anca D. Dragan
Establishing Appropriate Trust via Critical States. CoRR (2018)
Sandy H. Huang, Kush Bhatia, Pieter Abbeel, Anca D. Dragan
Establishing Appropriate Trust via Critical States. IROS (2018)
Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L. Bartlett, Martin J. Wainwright
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems. CoRR (2018)
Aditya Kusupati, Manish Singh, Kush Bhatia, Ashish Kumar, Prateek Jain, Manik Varma
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network. NeurIPS (2018)
Kush Bhatia, Aldo Pacchiano, Nicolas Flammarion, Peter L. Bartlett, Michael I. Jordan
Gen-Oja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation. CoRR (2018)
Kush Bhatia, Aldo Pacchiano, Nicolas Flammarion, Peter L. Bartlett, Michael I. Jordan
Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation. NeurIPS (2018)
Kush Bhatia, Prateek Jain, Parameswaran Kamalaruban, Purushottam Kar
Consistent Robust Regression. NIPS (2017)
Kush Bhatia, Prateek Jain, Parameswaran Kamalaruban, Purushottam Kar
Efficient and Consistent Robust Time Series Analysis. CoRR (2016)
Dinesh Khandelwal, Kush Bhatia, Chetan Arora, Parag Singla
Lazy Generic Cuts. Comput. Vis. Image Underst. 143 (2016)
Kush Bhatia, Himanshu Jain, Purushottam Kar, Prateek Jain, Manik Varma
Locally Non-linear Embeddings for Extreme Multi-label Learning. CoRR (2015)
Kush Bhatia, Prateek Jain, Purushottam Kar
Robust Regression via Hard Thresholding. NIPS (2015)
Kush Bhatia, Himanshu Jain, Purushottam Kar, Manik Varma, Prateek Jain
Sparse Local Embeddings for Extreme Multi-label Classification. NIPS (2015)
Kush Bhatia, Prateek Jain, Purushottam Kar
Robust Regression via Hard Thresholding. CoRR (2015)