Prateek Jain - RankMe

260 papers A* 79A 9B 3Misc 1Journal 128Unranked 39

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FastLane: Efficient Routed Systems for Late-Interaction Retrieval. CoRR Ramnath Kumar, Prateek Jain, Cho-Jui Hsieh
2025	J	`jnl`	Compressing Many-Shots in In-Context Learning. CoRR Devvrit Khatri, Pranamya Kulkarni, Nilesh Gupta, Yerram Varun, Liqian Peng, Jay Yagnik, Praneeth Netrapalli, Cho-Jui Hsieh, Alec Go, Inderjit S. Dhillon, Aditya Kusupati, Prateek Jain
2025	A*	`conf`	Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts? ICLR Sravanti Addepalli, Yerram Varun, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain
2025	J	`jnl`	Faster Approx. Top-K: Harnessing the Full Power of Two Stages. CoRR Yashas Samaga, Varun Yerram, Spandana Raj Babbula, Prateek Jain, Praneeth Netrapalli
2025	J	`jnl`	Interleaved Gibbs Diffusion for Constrained Generation. CoRR Gautham Govind Anil, Sachin Yadav, Dheeraj Nagaraj, Karthikeyan Shanmugam, Prateek Jain
2025	A*	`conf`	Masked Generative Nested Transformers with Decode Time Scaling. ICML Sahil Goyal, Debapriya Tula, Gagan Jain, Pradeep Shenoy, Prateek Jain, Sujoy Paul
2025	J	`jnl`	Masked Generative Nested Transformers with Decode Time Scaling. CoRR Sahil Goyal, Debapriya Tula, Gagan Jain, Pradeep Shenoy, Prateek Jain, Sujoy Paul
2025	—	`conf`	Matryoshka Model Learning for Improved Elastic Student Models. KDD (2) Chetan Verma, Aditya Srinivas Timmaraju, Cho-Jui Hsieh, Suyash Damle, Ngot Bui, Yang Zhang, Wen Chen, Xin Liu, Prateek Jain, Inderjit S. Dhillon
2025	J	`jnl`	Matryoshka Model Learning for Improved Elastic Student Models. CoRR Chetan Verma, Aditya Srinivas Timmaraju, Cho-Jui Hsieh, Suyash Damle, Ngot Bui, Yang Zhang, Wen Chen, Xin Liu, Prateek Jain, Inderjit S. Dhillon
2025	A*	`conf`	Matryoshka Quantization. ICML Pranav Ajit Nair, Puranjay Datta, Jeff Dean, Prateek Jain, Aditya Kusupati
2025	J	`jnl`	Matryoshka Quantization. CoRR Pranav Ajit Nair, Puranjay Datta, Jeff Dean, Prateek Jain, Aditya Kusupati
2025	J	`jnl`	Spark Transformer: Reactivating Sparsity in FFN and Attention. CoRR Chong You, Kan Wu, Zhipeng Jia, Lin Chen, Srinadh Bhojanapalli, Jiaxian Guo, Utku Evci, Jan Wassenberg, Praneeth Netrapalli, Jeremiah J. Willcock, Suvinay Subramanian, Felix Chern, Alek Andreev, Shreya Pathak, Felix X. Yu, Prateek Jain, David E. Culler, Henry M. Levy, Sanjiv Kumar
2024	J	`jnl`	Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts? CoRR Sravanti Addepalli, Yerram Varun, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain
2024	A*	`conf`	Dual-Encoders for Extreme Multi-label Classification. ICLR Nilesh Gupta, Devvrit, Ankit Singh Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit S. Dhillon
2024	J	`jnl`	EHI: End-to-end Learning of Hierarchical Index for Efficient Dense Retrieval. Trans. Mach. Learn. Res. Ramnath Kumar, Anshul Mittal, Nilesh Gupta, Aditya Kusupati, Inderjit S. Dhillon, Prateek Jain
2024	—	`conf`	End-to-End Neural Network Compression via l1/l2 Regularized Latency Surrogates. CVPR Workshops Anshul Nasery, Hardik Shah, Arun Sai Suggala, Prateek Jain
2024	J	`jnl`	Gecko: Versatile Text Embeddings Distilled from Large Language Models. CoRR Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, Blair Chen, Daniel Cer, Jeremy R. Cole, Kai Hui, Michael Boratko, Rajvi Kapadia, Wen Ding, Yi Luan, Sai Meher Karthik Duddu, Gustavo Hernández Ábrego, Weiqiang Shi, Nithi Gupta, Aditya Kusupati, Prateek Jain, Siddhartha Reddy Jonnalagadda, Ming-Wei Chang, Iftekhar Naim
2024	J	`jnl`	HiRE: High Recall Approximate Top-k Estimation for Efficient LLM Inference. CoRR Yashas Samaga, Varun Yerram, Chong You, Srinadh Bhojanapalli, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli
2024	—	`conf`	LookupViT: Compressing Visual Information to a Limited Number of Tokens. ECCV (86) Rajat Koner, Gagan Jain, Prateek Jain, Volker Tresp, Sujoy Paul
2024	J	`jnl`	LookupViT: Compressing visual information to a limited number of tokens. CoRR Rajat Koner, Gagan Jain, Prateek Jain, Volker Tresp, Sujoy Paul
2024	A*	`conf`	MatFormer: Nested Transformer for Elastic Inference. NeurIPS Devvrit, Sneha Kudugunta, Aditya Kusupati, Tim Dettmers, Kaifeng Chen, Inderjit S. Dhillon, Yulia Tsvetkov, Hanna Hajishirzi, Sham M. Kakade, Ali Farhadi, Prateek Jain
2024	A*	`conf`	Mixture of Nested Experts: Adaptive Processing of Visual Tokens. NeurIPS Gagan Jain, Nidhi Hegde, Aditya Kusupati, Arsha Nagrani, Shyamal Buch, Prateek Jain, Anurag Arnab, Sujoy Paul
2024	J	`jnl`	Mixture of Nested Experts: Adaptive Processing of Visual Tokens. CoRR Gagan Jain, Nidhi Hegde, Aditya Kusupati, Arsha Nagrani, Shyamal Buch, Prateek Jain, Anurag Arnab, Sujoy Paul
2024	A	`conf`	Sample-Efficient Personalization: Modeling User Parameters as Low Rank Plus Sparse Components. AISTATS Soumyabrata Pal, Prateek Varshney, Gagan Madan, Prateek Jain, Abhradeep Thakurta, Gaurav Aggarwal, Pradeep Shenoy, Gaurav Srivastava
2024	A*	`conf`	Tandem Transformers for Inference Efficient LLMs. ICML Aishwarya P. S., Pranav Ajit Nair, Yashas Samaga, Toby Boyd, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli
2024	J	`jnl`	Tandem Transformers for Inference Efficient LLMs. CoRR Aishwarya P. S., Pranav Ajit Nair, Yashas Samaga, Toby Boyd, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli
2024	A*	`conf`	Time-Reversal Provides Unsupervised Feedback to LLMs. NeurIPS Yerram Varun, Rahul Madhavan, Sravanti Addepalli, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain
2024	J	`jnl`	Time-Reversal Provides Unsupervised Feedback to LLMs. CoRR Yerram Varun, Rahul Madhavan, Sravanti Addepalli, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain
2023	A*	`conf`	AdANNS: A Framework for Adaptive Semantic Search. NeurIPS Aniket Rege, Aditya Kusupati, Sharan Ranjit S, Alan Fan, Qingqing Cao, Sham M. Kakade, Prateek Jain, Ali Farhadi
2023	J	`jnl`	AdANNS: A Framework for Adaptive Semantic Search. CoRR Aniket Rege, Aditya Kusupati, Sharan Ranjit S, Alan Fan, Qingqing Cao, Sham M. Kakade, Prateek Jain, Ali Farhadi
2023	A*	`conf`	Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints. NeurIPS Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain
2023	J	`jnl`	Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints. CoRR Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain
2023	J	`jnl`	EHI: End-to-end Learning of Hierarchical Index for Efficient Dense Retrieval. CoRR Ramnath Kumar, Anshul Mittal, Nilesh Gupta, Aditya Kusupati, Inderjit S. Dhillon, Prateek Jain
2023	J	`jnl`	Efficacy of Dual-Encoders for Extreme Multi-Label Classification. CoRR Nilesh Gupta, Devvrit Khatri, Ankit Singh Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit S. Dhillon
2023	J	`jnl`	End-to-End Neural Network Compression via 𝓁 CoRR Anshul Nasery, Hardik Shah, Arun Sai Suggala, Prateek Jain
2023	A*	`conf`	Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks. ICLR Sravanti Addepalli, Anshul Nasery, Venkatesh Babu Radhakrishnan, Praneeth Netrapalli, Prateek Jain
2023	A*	`conf`	Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency. NeurIPS Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala
2023	J	`jnl`	MatFormer: Nested Transformer for Elastic Inference. CoRR Devvrit, Sneha Kudugunta, Aditya Kusupati, Tim Dettmers, Kaifeng Chen, Inderjit S. Dhillon, Yulia Tsvetkov, Hannaneh Hajishirzi, Sham M. Kakade, Ali Farhadi, Prateek Jain
2023	A*	`conf`	Multi-Task Differential Privacy Under Distribution Skew. ICML Walid Krichene, Prateek Jain, Shuang Song, Mukund Sundararajan, Abhradeep Guha Thakurta, Li Zhang
2023	J	`jnl`	Multi-Task Differential Privacy Under Distribution Skew. CoRR Walid Krichene, Prateek Jain, Shuang Song, Mukund Sundararajan, Abhradeep Thakurta, Li Zhang
2023	A*	`conf`	Multi-User Reinforcement Learning with Low Rank Rewards. ICML Dheeraj Mysore Nagaraj, Suhas S. Kowshik, Naman Agarwal, Praneeth Netrapalli, Prateek Jain
2023	J	`jnl`	Near Optimal Private and Robust Linear Regression. CoRR Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala
2023	A*	`conf`	Online Low Rank Matrix Completion. ICLR Soumyabrata Pal, Prateek Jain
2023	A	`conf`	Optimal Algorithms for Latent Bandits with Cluster Structure. AISTATS Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain
2023	J	`jnl`	Optimal Algorithms for Latent Bandits with Cluster Structure. CoRR Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain
2023	A*	`conf`	Simplicity Bias in 1-Hidden Layer Neural Networks. NeurIPS Depen Morwani, Jatin Batra, Prateek Jain, Praneeth Netrapalli
2023	J	`jnl`	Simplicity Bias in 1-Hidden Layer Neural Networks. CoRR Depen Morwani, Jatin Batra, Prateek Jain, Praneeth Netrapalli
2023	A*	`conf`	Treeformer: Dense Gradient Trees for Efficient Attention Computation. ICLR Lovish Madaan, Srinadh Bhojanapalli, Himanshu Jain, Prateek Jain
2022	A*	`conf`	(Nearly) Optimal Private Linear Regression for Sub-Gaussian Data via Adaptive Clipping. COLT Prateek Varshney, Abhradeep Thakurta, Prateek Jain
2022	J	`jnl`	(Nearly) Optimal Private Linear Regression via Adaptive Clipping. CoRR Prateek Varshney, Abhradeep Thakurta, Prateek Jain
2022	J	`jnl`	DAFT: Distilling Adversarially Fine-tuned Models for Better OOD Generalization. CoRR Anshul Nasery, Sravanti Addepalli, Praneeth Netrapalli, Prateek Jain
2022	A*	`conf`	DP-PCA: Statistically Optimal and Differentially Private PCA. NeurIPS Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh
2022	J	`jnl`	DP-PCA: Statistically Optimal and Differentially Private PCA. CoRR Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh
2022	A*	`conf`	IGLU: Efficient GCN Training via Lazy Updates. ICLR S. Deepak Narayanan, Aditya Sinha, Prateek Jain, Purushottam Kar, Sundararajan Sellamanickam
2022	J	`jnl`	Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent. Trans. Mach. Learn. Res. Ajaykrishna Karthikeyan, Naman Jain, Nagarajan Natarajan, Prateek Jain
2022	J	`jnl`	Learning an Invertible Output Mapping Can Mitigate Simplicity Bias in Neural Networks. CoRR Sravanti Addepalli, Anshul Nasery, R. Venkatesh Babu, Praneeth Netrapalli, Prateek Jain
2022	J	`jnl`	MET: Masked Encoding for Tabular Data. CoRR Kushal Majmundar, Sachin Goyal, Praneeth Netrapalli, Prateek Jain
2022	A*	`conf`	Matryoshka Representation Learning. NeurIPS Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham M. Kakade, Prateek Jain, Ali Farhadi
2022	J	`jnl`	Matryoshka Representations for Adaptive Deployment. CoRR Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham M. Kakade, Prateek Jain, Ali Farhadi
2022	J	`jnl`	Multi-User Reinforcement Learning with Low Rank Rewards. CoRR Naman Agarwal, Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli
2022	J	`jnl`	Online Low Rank Matrix Completion. CoRR Prateek Jain, Soumyabrata Pal
2022	A*	`conf`	Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs. ICLR Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Mysore Nagaraj, Praneeth Netrapalli
2022	J	`jnl`	Private and Efficient Meta-Learning with Low Rank and Sparse Decomposition. CoRR Soumyabrata Pal, Prateek Varshney, Prateek Jain, Abhradeep Guha Thakurta, Gagan Madan, Gaurav Aggarwal, Pradeep Shenoy, Gaurav Srivastava
2022	A*	`conf`	Reproducibility in Optimization: Theoretical Framework and Limits. NeurIPS Kwangjun Ahn, Prateek Jain, Ziwei Ji, Satyen Kale, Praneeth Netrapalli, Gil I. Shamir
2022	J	`jnl`	Reproducibility in Optimization: Theoretical Framework and Limits. CoRR Kwangjun Ahn, Prateek Jain, Ziwei Ji, Satyen Kale, Praneeth Netrapalli, Gil I. Shamir
2022	A	`conf`	Robust Training in High Dimensions via Block Coordinate Geometric Median Descent. AISTATS Anish Acharya, Abolfazl Hashemi, Prateek Jain, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu
2022	A*	`conf`	S3GC: Scalable Self-Supervised Graph Clustering. NeurIPS Devvrit, Aditya Sinha, Inderjit S. Dhillon, Prateek Jain
2022	J	`jnl`	Treeformer: Dense Gradient Trees for Efficient Attention Computation. CoRR Lovish Madaan, Srinadh Bhojanapalli, Himanshu Jain, Prateek Jain
2021	A*	`conf`	Differentially Private Model Personalization. NeurIPS Prateek Jain, John Rush, Adam D. Smith, Shuang Song, Abhradeep Guha Thakurta
2021	A*	`conf`	Do Input Gradients Highlight Discriminative Features? NeurIPS Harshay Shah, Prateek Jain, Praneeth Netrapalli
2021	J	`jnl`	Do Input Gradients Highlight Discriminative Features? CoRR Harshay Shah, Prateek Jain, Praneeth Netrapalli
2021	J	`jnl`	IGLU: Efficient GCN Training via Lazy Updates. CoRR S. Deepak Narayanan, Aditya Sinha, Prateek Jain, Purushottam Kar, Sundararajan Sellamanickam
2021	A*	`conf`	LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes. NeurIPS Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham M. Kakade, Ali Farhadi
2021	J	`jnl`	LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes. CoRR Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham M. Kakade, Ali Farhadi
2021	J	`jnl`	Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent. CoRR Ajaykrishna Karthikeyan, Naman Jain, Nagarajan Natarajan, Prateek Jain
2021	J	`jnl`	Making the Last Iterate of SGD Information Theoretically Optimal. SIAM J. Optim. Prateek Jain, Dheeraj M. Nagaraj, Praneeth Netrapalli
2021	A*	`conf`	Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems. NeurIPS Suhas S. Kowshik, Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli
2021	J	`jnl`	Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems. CoRR Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli
2021	J	`jnl`	Node-Level Differentially Private Graph Neural Networks. CoRR Ameya Daigavane, Gagan Madan, Aditya Sinha, Abhradeep Guha Thakurta, Gaurav Aggarwal, Prateek Jain
2021	J	`jnl`	Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs. CoRR Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli
2021	J	`jnl`	Optimal Regret Algorithm for Pseudo-1d Bandit Convex Optimization. CoRR Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain
2021	A*	`conf`	Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization. ICML Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain
2021	A*	`conf`	Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates. ICML Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
2021	J	`jnl`	Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates. CoRR Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang
2021	J	`jnl`	Robust Training in High Dimensions via Block Coordinate Geometric Median Descent. CoRR Anish Acharya, Abolfazl Hashemi, Prateek Jain, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu
2021	J	`jnl`	Sample Efficient Linear Meta-Learning by Alternating Minimization. CoRR Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
2021	A*	`conf`	Statistically and Computationally Efficient Linear Meta-representation Learning. NeurIPS Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
2021	A*	`conf`	Streaming Linear System Identification with Reverse Experience Replay. NeurIPS Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli
2021	J	`jnl`	Streaming Linear System Identification with Reverse Experience Replay. CoRR Prateek Jain, Suhas S. Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli
2020	A*	`conf`	DROCC: Deep Robust One-Class Classification. ICML Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain
2020	J	`jnl`	DROCC: Deep Robust One-Class Classification. CoRR Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain
2020	J	`jnl`	Globally-convergent Iteratively Reweighted Least Squares for Robust Regression Problems. CoRR Bhaskar Mukhoty, Govind Gopakumar, Prateek Jain, Purushottam Kar
2020	A*	`conf`	Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms. NeurIPS Dheeraj Nagaraj, Xian Wu, Guy Bresler, Prateek Jain, Praneeth Netrapalli
2020	J	`jnl`	Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms. CoRR Guy Bresler, Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli, Xian Wu
2020	J	`jnl`	Nonconvex Optimization for Signal Processing and Machine Learning [From the Guest Editors]. IEEE Signal Process. Mag. Anthony Man-Cho So, Prateek Jain, Wing-Kin Ma, Gesualdo Scutari
2020	J	`jnl`	Programming by Rewards. CoRR Nagarajan Natarajan, Ajaykrishna Karthikeyan, Prateek Jain, Ivan Radicek, Sriram K. Rajamani, Sumit Gulwani, Johannes Gehrke
2020	A*	`conf`	Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method. NeurIPS Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
2020	J	`jnl`	Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method. CoRR Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
2020	A*	`conf`	RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference. NeurIPS Oindrila Saha, Aditya Kusupati, Harsha Vardhan Simhadri, Manik Varma, Prateek Jain
2020	J	`jnl`	RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference. CoRR Oindrila Saha, Aditya Kusupati, Harsha Vardhan Simhadri, Manik Varma, Prateek Jain
2020	A*	`conf`	Soft Threshold Weight Reparameterization for Learnable Sparsity. ICML Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi
2020	J	`jnl`	Soft Threshold Weight Reparameterization for Learnable Sparsity. CoRR Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi
2020	A*	`conf`	The Pitfalls of Simplicity Bias in Neural Networks. NeurIPS Harshay Shah, Kaustav Tamuly, Aditi Raghunathan, Prateek Jain, Praneeth Netrapalli
2020	J	`jnl`	The Pitfalls of Simplicity Bias in Neural Networks. CoRR Harshay Shah, Kaustav Tamuly, Aditi Raghunathan, Prateek Jain, Praneeth Netrapalli
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	A	`conf`	Cost aware Inference for IoT Devices. AISTATS Pengkai Zhu, Durmus Alp Emre Acar, Nan Feng, Prateek Jain, Venkatesh Saligrama
2019	A*	`conf`	Distributional Semantics Meets Multi-Label Learning. AAAI Vivek Gupta, Rahul Wadbude, Nagarajan Natarajan, Harish Karnick, Prateek Jain, Piyush Rai
2019	A*	`conf`	Efficient Algorithms for Smooth Minimax Optimization. NeurIPS Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
2019	J	`jnl`	Efficient Algorithms for Smooth Minimax Optimization. CoRR Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
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`	GesturePod: Enabling On-device Gesture-based Interaction for White Cane Users. UIST Shishir G. Patil, Don Kurian Dennis, Chirag Pabbaraju, Nadeem Shaheer, Harsha Vardhan Simhadri, Vivek Seshadri, Manik Varma, Prateek Jain
2019	A	`conf`	Globally-convergent Iteratively Reweighted Least Squares for Robust Regression Problems. AISTATS Bhaskar Mukhoty, Govind Gopakumar, Prateek Jain, Purushottam Kar
2019	J	`jnl`	Learning Functions over Sets via Permutation Adversarial Networks. CoRR Chirag Pabbaraju, Prateek Jain
2019	A	`conf`	Learning Natural Programs from a Few Examples in Real-Time. AISTATS Nagarajan Natarajan, Danny Simmons, Naren Datha, Prateek Jain, Sumit Gulwani
2019	A*	`conf`	Making the Last Iterate of SGD Information Theoretically Optimal. COLT Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli
2019	J	`jnl`	Making the Last Iterate of SGD Information Theoretically Optimal. CoRR Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli
2019	J	`jnl`	OASIS: ILP-Guided Synthesis of Loop Invariants. CoRR Sahil Bhatia, Saswat Padhi, Nagarajan Natarajan, Rahul Sharma, Prateek Jain
2019	A*	`conf`	Open Problem: Do Good Algorithms Necessarily Query Bad Points? COLT Rong Ge, Prateek Jain, Sham M. Kakade, Rahul Kidambi, Dheeraj M. Nagaraj, Praneeth Netrapalli
2019	A*	`conf`	Provable Non-linear Inductive Matrix Completion. NeurIPS Kai Zhong, Zhao Song, Prateek Jain, Inderjit S. Dhillon
2019	A*	`conf`	SGD without Replacement: Sharper Rates for General Smooth Convex Functions. ICML Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli
2019	J	`jnl`	SGD without Replacement: Sharper Rates for General Smooth Convex Functions. CoRR Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli
2019	A*	`conf`	Shallow RNN: Accurate Time-series Classification on Resource Constrained Devices. NeurIPS Don Kurian Dennis, Durmus Alp Emre Acar, Vikram Mandikal, Vinu Sankar Sadasivan, Venkatesh Saligrama, Harsha Vardhan Simhadri, Prateek Jain
2018	A*	`conf`	Accelerating Stochastic Gradient Descent for Least Squares Regression. COLT Prateek Jain, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli, Aaron Sidford
2018	A*	`conf`	Differentially Private Matrix Completion Revisited. ICML Prateek Jain, Om Dipakbhai Thakkar, Abhradeep Thakurta
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`	FlashProfile: a framework for synthesizing data profiles. Proc. ACM Program. Lang. Saswat Padhi, Prateek Jain, Daniel Perelman, Oleksandr Polozov, Sumit Gulwani, Todd D. Millstein
2018	A*	`conf`	Multiple Instance Learning for Efficient Sequential Data Classification on Resource-constrained Devices. NeurIPS Don Kurian Dennis, Chirag Pabbaraju, Harsha Vardhan Simhadri, Prateek Jain
2018	—	`conf`	Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples. ICLR (Poster) Ashwin Kalyan, Abhishek Mohta, Oleksandr Polozov, Dhruv Batra, Prateek Jain, Sumit Gulwani
2018	J	`jnl`	Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples. CoRR Ashwin J. Vijayakumar, Abhishek Mohta, Oleksandr Polozov, Dhruv Batra, Prateek Jain, Sumit Gulwani
2018	J	`jnl`	Nonlinear Inductive Matrix Completion based on One-layer Neural Networks. CoRR Kai Zhong, Zhao Song, Prateek Jain, Inderjit S. Dhillon
2018	Misc	`conf`	On the Insufficiency of Existing Momentum Schemes for Stochastic Optimization. ITA Rahul Kidambi, Praneeth Netrapalli, Prateek Jain, Sham M. Kakade
2018	—	`conf`	On the insufficiency of existing momentum schemes for Stochastic Optimization. ICLR Rahul Kidambi, Praneeth Netrapalli, Prateek Jain, Sham M. Kakade
2018	J	`jnl`	On the insufficiency of existing momentum schemes for Stochastic Optimization. CoRR Rahul Kidambi, Praneeth Netrapalli, Prateek Jain, Sham M. Kakade
2018	A*	`conf`	Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form. COLT Srinadh Bhojanapalli, Nicolas Boumal, Prateek Jain, Praneeth Netrapalli
2018	J	`jnl`	Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form. CoRR Srinadh Bhojanapalli, Nicolas Boumal, Prateek Jain, Praneeth Netrapalli
2018	A*	`conf`	Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds. NeurIPS Raghav Somani, Chirag Gupta, Prateek Jain, Praneeth Netrapalli
2017	—	`conf`	A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares). FSTTCS Prateek Jain, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli, Venkata Krishna Pillutla, Aaron Sidford
2017	J	`jnl`	A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares). CoRR Prateek Jain, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli, Venkata Krishna Pillutla, Aaron Sidford
2017	J	`jnl`	Accelerating Stochastic Gradient Descent. CoRR Prateek Jain, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli, Aaron Sidford
2017	A*	`conf`	Active Heteroscedastic Regression. ICML Kamalika Chaudhuri, Prateek Jain, Nagarajan Natarajan
2017	—	`conf`	Consistent Robust Regression. NIPS Kush Bhatia, Prateek Jain, Parameswaran Kamalaruban, Purushottam Kar
2017	J	`jnl`	Differentially Private Matrix Completion, Revisited. CoRR Prateek Jain, Om Thakkar, Abhradeep Thakurta
2017	A*	`conf`	Fast second-order cone programming for safe mission planning. ICRA Kai Zhong, Prateek Jain, Ashish Kapoor
2017	J	`jnl`	FlashProfile: Interactive Synthesis of Syntactic Profiles. CoRR Saswat Padhi, Prateek Jain, Daniel Perelman, Oleksandr Polozov, Sumit Gulwani, Todd D. Millstein
2017	A	`conf`	Global Convergence of Non-Convex Gradient Descent for Computing Matrix Squareroot. AISTATS Prateek Jain, Chi Jin, Sham M. Kakade, Praneeth Netrapalli
2017	—	`conf`	Learning Mixture of Gaussians with Streaming Data. NIPS Aditi Raghunathan, Prateek Jain, Ravishankar Krishnaswamy
2017	J	`jnl`	Learning Mixture of Gaussians with Streaming Data. CoRR Aditi Raghunathan, Ravishankar Krishnaswamy, Prateek Jain
2017	A*	`conf`	Nearly Optimal Robust Matrix Completion. ICML Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain
2017	J	`jnl`	Non-convex Optimization for Machine Learning. CoRR Prateek Jain, Purushottam Kar
2017	J	`jnl`	Non-convex Optimization for Machine Learning. Found. Trends Mach. Learn. Prateek Jain, Purushottam Kar
2017	J	`jnl`	Parallelizing Stochastic Gradient Descent for Least Squares Regression: Mini-batching, Averaging, and Model Misspecification. J. Mach. Learn. Res. Prateek Jain, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli, Aaron Sidford
2017	J	`jnl`	Partial Hard Thresholding. IEEE Trans. Inf. Theory Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon
2017	B	`conf`	Programming by Examples: PL Meets ML. APLAS Sumit Gulwani, Prateek Jain
2017	A*	`conf`	ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices. ICML Chirag Gupta, Arun Sai Suggala, Ankit Goyal, Harsha Vardhan Simhadri, Bhargavi Paranjape, Ashish Kumar, Saurabh Goyal, Raghavendra Udupa, Manik Varma, Prateek Jain
2017	A*	`conf`	Recovery Guarantees for One-hidden-layer Neural Networks. ICML Kai Zhong, Zhao Song, Prateek Jain, Peter L. Bartlett, Inderjit S. Dhillon
2017	J	`jnl`	Recovery Guarantees for One-hidden-layer Neural Networks. CoRR Kai Zhong, Zhao Song, Prateek Jain, Peter L. Bartlett, Inderjit S. Dhillon
2017	A*	`conf`	Scalable Optimization of Multivariate Performance Measures in Multi-instance Multi-label Learning. AAAI Apoorv Aggarwal, Sandip Ghoshal, Ankith M. S. Shetty, Suhit Sinha, Ganesh Ramakrishnan, Purushottam Kar, Prateek Jain
2017	A*	`conf`	Thresholding Based Outlier Robust PCA. COLT Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli
2017	J	`jnl`	Thresholding based Efficient Outlier Robust PCA. CoRR Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli
2016	B	`conf`	Diverse Yet Efficient Retrieval using Locality Sensitive Hashing. ICMR Vidyadhar Rao, Prateek Jain, C. V. Jawahar
2016	J	`jnl`	Efficient and Consistent Robust Time Series Analysis. CoRR Kush Bhatia, Prateek Jain, Parameswaran Kamalaruban, Purushottam Kar
2016	J	`jnl`	Fast Second-order Cone Programming for Safe Mission Planning. CoRR Kai Zhong, Prateek Jain, Ashish Kapoor
2016	J	`jnl`	Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization. SIAM J. Optim. Alekh Agarwal, Animashree Anandkumar, Prateek Jain, Praneeth Netrapalli
2016	J	`jnl`	Matching Matrix Bernstein with Little Memory: Near-Optimal Finite Sample Guarantees for Oja's Algorithm. CoRR Prateek Jain, Chi Jin, Sham M. Kakade, Praneeth Netrapalli, Aaron Sidford
2016	—	`conf`	Mixed Linear Regression with Multiple Components. NIPS Kai Zhong, Prateek Jain, Inderjit S. Dhillon
2016	J	`jnl`	Nearly-optimal Robust Matrix Completion. CoRR Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain
2016	J	`jnl`	Parallelizing Stochastic Approximation Through Mini-Batching and Tail-Averaging. CoRR Prateek Jain, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli, Aaron Sidford
2016	—	`ed.`	Proceedings of the 3rd IKDD Conference on Data Science, CODS 2016, Pune, India, March 13-16, 2016 CODS Madhav V. Marathe, Mukesh K. Mohania, Mausam, Prateek Jain
2016	—	`conf`	Regret Bounds for Non-decomposable Metrics with Missing Labels. NIPS Nagarajan Natarajan, Prateek Jain
2016	J	`jnl`	Regret Bounds for Non-decomposable Metrics with Missing Labels. CoRR Prateek Jain, Nagarajan Natarajan
2016	—	`conf`	Selective inference for group-sparse linear models. NIPS Fan Yang, Rina Foygel Barber, Prateek Jain, John D. Lafferty
2016	A*	`conf`	Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm. COLT Prateek Jain, Chi Jin, Sham M. Kakade, Praneeth Netrapalli, Aaron Sidford
2016	—	`conf`	Structured Sparse Regression via Greedy Hard Thresholding. NIPS Prateek Jain, Nikhil Rao, Inderjit S. Dhillon
2016	J	`jnl`	Structured Sparse Regression via Greedy Hard-Thresholding. CoRR Prateek Jain, Nikhil Rao, Inderjit S. Dhillon
2016	A	`conf`	Tensor vs. Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations. AISTATS Anima Anandkumar, Prateek Jain, Yang Shi, U. N. Niranjan
2015	—	`conf`	Alternating Minimization for Regression Problems with Vector-valued Outputs. NIPS Prateek Jain, Ambuj Tewari
2015	J	`jnl`	Computing Matrix Squareroot via Non Convex Local Search. CoRR Prateek Jain, Chi Jin, Sham M. Kakade, Praneeth Netrapalli
2015	J	`jnl`	Diverse Yet Efficient Retrieval using Hash Functions. CoRR Vidyadhar Rao, Prateek Jain, C. V. Jawahar
2015	B	`conf`	Efficient Matrix Sensing Using Rank-1 Gaussian Measurements. ALT Kai Zhong, Prateek Jain, Inderjit S. Dhillon
2015	A*	`conf`	Fast Exact Matrix Completion with Finite Samples. COLT Prateek Jain, Praneeth Netrapalli
2015	J	`jnl`	Locally Non-linear Embeddings for Extreme Multi-label Learning. CoRR Kush Bhatia, Himanshu Jain, Purushottam Kar, Prateek Jain, Manik Varma
2015	A*	`conf`	Optimizing Non-decomposable Performance Measures: A Tale of Two Classes. ICML Harikrishna Narasimhan, Purushottam Kar, Prateek Jain
2015	J	`jnl`	Optimizing Non-decomposable Performance Measures: A Tale of Two Classes. CoRR Harikrishna Narasimhan, Purushottam Kar, Prateek Jain
2015	J	`jnl`	Phase Retrieval Using Alternating Minimization. IEEE Trans. Signal Process. Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi
2015	—	`conf`	Predtron: A Family of Online Algorithms for General Prediction Problems. NIPS Prateek Jain, Nagarajan Natarajan, Ambuj Tewari
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
2015	A*	`conf`	Surrogate Functions for Maximizing Precision at the Top. ICML Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
2015	J	`jnl`	Surrogate Functions for Maximizing Precision at the Top. CoRR Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
2015	J	`jnl`	Tensor vs Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations. CoRR Animashree Anandkumar, Prateek Jain, Yang Shi, U. N. Niranjan
2015	A*	`conf`	Tighter Low-rank Approximation via Sampling the Leveraged Element. SODA Srinadh Bhojanapalli, Prateek Jain, Sujay Sanghavi
2015	J	`jnl`	To Drop or Not to Drop: Robustness, Consistency and Differential Privacy Properties of Dropout. CoRR Prateek Jain, Vivek Kulkarni, Abhradeep Thakurta, Oliver Williams
2014	A*	`conf`	(Near) Dimension Independent Risk Bounds for Differentially Private Learning. ICML Prateek Jain, Abhradeep Guha Thakurta
2014	J	`jnl`	Fast Exact Matrix Completion with Finite Samples. CoRR Prateek Jain, Praneeth Netrapalli
2014	J	`jnl`	Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning. IEEE Trans. Pattern Anal. Mach. Intell. Sudheendra Vijayanarasimhan, Prateek Jain, Kristen Grauman
2014	A*	`conf`	Large-scale Multi-label Learning with Missing Labels. ICML Hsiang-Fu Yu, Prateek Jain, Purushottam Kar, Inderjit S. Dhillon
2014	A*	`conf`	Learning Mixtures of Discrete Product Distributions using Spectral Decompositions. COLT Prateek Jain, Sewoong Oh
2014	A*	`conf`	Learning Sparsely Used Overcomplete Dictionaries. COLT Alekh Agarwal, Animashree Anandkumar, Prateek Jain, Praneeth Netrapalli, Rashish Tandon
2014	—	`conf`	Non-convex Robust PCA. NIPS Praneeth Netrapalli, U. N. Niranjan, Sujay Sanghavi, Animashree Anandkumar, Prateek Jain
2014	J	`jnl`	Non-convex Robust PCA. CoRR Praneeth Netrapalli, U. N. Niranjan, Sujay Sanghavi, Animashree Anandkumar, Prateek Jain
2014	—	`conf`	On Iterative Hard Thresholding Methods for High-dimensional M-Estimation. NIPS Prateek Jain, Ambuj Tewari, Purushottam Kar
2014	J	`jnl`	On Iterative Hard Thresholding Methods for High-dimensional M-Estimation. CoRR Prateek Jain, Ambuj Tewari, Purushottam Kar
2014	—	`conf`	Online and Stochastic Gradient Methods for Non-decomposable Loss Functions. NIPS Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
2014	J	`jnl`	Online and Stochastic Gradient Methods for Non-decomposable Loss Functions. CoRR Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
2014	—	`conf`	Provable Submodular Minimization using Wolfe's Algorithm. NIPS Deeparnab Chakrabarty, Prateek Jain, Pravesh Kothari
2014	J	`jnl`	Provable Submodular Minimization using Wolfe's Algorithm. CoRR Deeparnab Chakrabarty, Prateek Jain, Pravesh Kothari
2014	—	`conf`	Provable Tensor Factorization with Missing Data. NIPS Prateek Jain, Sewoong Oh
2014	J	`jnl`	Tighter Low-rank Approximation via Sampling the Leveraged Element. CoRR Srinadh Bhojanapalli, Prateek Jain, Sujay Sanghavi
2014	A*	`conf`	Universal Matrix Completion. ICML Srinadh Bhojanapalli, Prateek Jain
2014	J	`jnl`	Universal Matrix Completion. CoRR Srinadh Bhojanapalli, Prateek Jain
2013	A*	`conf`	Ad impression forecasting for sponsored search. WWW Abhirup Nath, Shibnath Mukherjee, Prateek Jain, Navin Goyal, Srivatsan Laxman
2013	—	`conf`	Differentially Private Learning with Kernels. ICML (3) Prateek Jain, Abhradeep Thakurta
2013	J	`jnl`	Improved Multiple Sequence Alignments Using Coupled Pattern Mining. IEEE ACM Trans. Comput. Biol. Bioinform. K. S. M. Tozammel Hossain, Debprakash Patnaik, Srivatsan Laxman, Prateek Jain, Chris Bailey-Kellogg, Naren Ramakrishnan
2013	J	`jnl`	Large-scale Multi-label Learning with Missing Labels. CoRR Hsiang-Fu Yu, Prateek Jain, Inderjit S. Dhillon
2013	J	`jnl`	Learning Mixtures of Discrete Product Distributions using Spectral Decompositions. CoRR Prateek Jain, Sewoong Oh
2013	J	`jnl`	Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization. CoRR Alekh Agarwal, Animashree Anandkumar, Prateek Jain, Praneeth Netrapalli, Rashish Tandon
2013	A*	`conf`	Low-rank matrix completion using alternating minimization. STOC Prateek Jain, Praneeth Netrapalli, Sujay Sanghavi
2013	—	`conf`	Memory Limited, Streaming PCA. NIPS Ioannis Mitliagkas, Constantine Caramanis, Prateek Jain
2013	J	`jnl`	Memory Limited, Streaming PCA. CoRR Ioannis Mitliagkas, Constantine Caramanis, Prateek Jain
2013	J	`jnl`	On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions CoRR Purushottam Kar, Bharath K. Sriperumbudur, Prateek Jain, Harish Karnick
2013	—	`conf`	On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions. ICML (3) Purushottam Kar, Bharath K. Sriperumbudur, Prateek Jain, Harish Karnick
2013	—	`conf`	One-Bit Compressed Sensing: Provable Support and Vector Recovery. ICML (3) Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya V. Nori
2013	—	`conf`	Phase Retrieval using Alternating Minimization. NIPS Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi
2013	J	`jnl`	Phase Retrieval using Alternating Minimization. CoRR Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi
2013	J	`jnl`	Provable Inductive Matrix Completion. CoRR Prateek Jain, Inderjit S. Dhillon
2012	A*	`conf`	Differentially Private Online Learning. COLT Prateek Jain, Pravesh Kothari, Abhradeep Thakurta
2012	—	`conf`	Improved multiple sequence alignments using coupled pattern mining. BCB K. S. M. Tozammel Hossain, Debprakash Patnaik, Srivatsan Laxman, Prateek Jain, Chris Bailey-Kellogg, Naren Ramakrishnan
2012	J	`jnl`	Low-rank Matrix Completion using Alternating Minimization CoRR Prateek Jain, Praneeth Netrapalli, Sujay Sanghavi
2012	J	`jnl`	Metric and Kernel Learning Using a Linear Transformation. J. Mach. Learn. Res. Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon
2012	—	`conf`	Mirror Descent Based Database Privacy. APPROX-RANDOM Prateek Jain, Abhradeep Thakurta
2012	—	`conf`	Multilabel Classification using Bayesian Compressed Sensing. NIPS Ashish Kapoor, Raajay Viswanathan, Prateek Jain
2012	J	`jnl`	Supervised Learning with Similarity Functions CoRR Purushottam Kar, Prateek Jain
2012	—	`conf`	Supervised Learning with Similarity Functions. NIPS Purushottam Kar, Prateek Jain
2012	J	`jnl`	The Interplay Between Stability and Regret in Online Learning CoRR Ankan Saha, Prateek Jain, Ambuj Tewari
2011	J	`jnl`	A Learning Framework for Self-Tuning Histograms CoRR Raajay Viswanathan, Prateek Jain, Srivatsan Laxman, Arvind Arasu
2011	J	`jnl`	Differentially Private Online Learning CoRR Prateek Jain, Pravesh Kothari, Abhradeep Thakurta
2011	J	`jnl`	Orthogonal Matching Pursuit with Replacement CoRR Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon
2011	—	`conf`	Orthogonal Matching Pursuit with Replacement. NIPS Prateek Jain, Ambuj Tewari, Inderjit S. Dhillon
2011	J	`jnl`	Similarity-based Learning via Data Driven Embeddings CoRR Purushottam Kar, Prateek Jain
2011	—	`conf`	Similarity-based Learning via Data Driven Embeddings. NIPS Purushottam Kar, Prateek Jain
2010	A*	`conf`	Far-sighted active learning on a budget for image and video recognition. CVPR Sudheendra Vijayanarasimhan, Prateek Jain, Kristen Grauman
2010	—	`conf`	Guaranteed Rank Minimization via Singular Value Projection. NIPS Prateek Jain, Raghu Meka, Inderjit S. Dhillon
2010	—	`conf`	Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning. NIPS Prateek Jain, Sudheendra Vijayanarasimhan, Kristen Grauman
2010	—	`conf`	Inductive Regularized Learning of Kernel Functions. NIPS Prateek Jain, Brian Kulis, Inderjit S. Dhillon
2009	A*	`conf`	Active learning for large multi-class problems. CVPR Prateek Jain, Ashish Kapoor
2009	J	`jnl`	Fast Similarity Search for Learned Metrics. IEEE Trans. Pattern Anal. Mach. Intell. Brian Kulis, Prateek Jain, Kristen Grauman
2009	A*	`conf`	Geometry-aware metric learning. ICML Zhengdong Lu, Prateek Jain, Inderjit S. Dhillon
2009	J	`jnl`	Guaranteed Rank Minimization via Singular Value Projection CoRR Raghu Meka, Prateek Jain, Inderjit S. Dhillon
2009	—	`conf`	Matrix Completion from Power-Law Distributed Samples. NIPS Raghu Meka, Prateek Jain, Inderjit S. Dhillon
2009	J	`jnl`	Metric and Kernel Learning using a Linear Transformation. CoRR Prateek Jain, Brian Kulis, Jason V. Davis, Inderjit S. Dhillon
2008	A*	`conf`	Fast image search for learned metrics. CVPR Prateek Jain, Brian Kulis, Kristen Grauman
2008	—	`conf`	Online Metric Learning and Fast Similarity Search. NIPS Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kristen Grauman
2008	A*	`conf`	Rank minimization via online learning. ICML Raghu Meka, Prateek Jain, Constantine Caramanis, Inderjit S. Dhillon
2008	A	`conf`	Simultaneous Unsupervised Learning of Disparate Clusterings. SDM Prateek Jain, Raghu Meka, Inderjit S. Dhillon
2008	J	`jnl`	Simultaneous Unsupervised Learning of Disparate Clusterings. Stat. Anal. Data Min. Prateek Jain, Raghu Meka, Inderjit S. Dhillon
2007	A*	`conf`	Information-theoretic metric learning. ICML Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit Sra, Inderjit S. Dhillon
2005	—	`conf`	Multi-objective Optimization for Adaptive Web Site Generation. PReMI Prateek Jain, Pabitra Mitra
2004	—	`conf`	Anaphora Resolution in Multi-Person Dialogues. SIGDIAL Workshop Prateek Jain, Manav Ratan Mital, Sumit Kumar, Amitabha Mukerjee, Achla M. Raina