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Prateek Jain

113 papers · 2008–2025 · 10 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (35) 🐝 Cross-Pollinator (14) πŸƒ Academic Marathon (17) 🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (7) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌟 Keyword Trendsetter Combo (10) 🏠 Conference Loyalist (53) πŸ† Keyword Champion (3) πŸ”¬ Deep Specialist (14) 🀝 Dynamic Duo (31) πŸ† Grand Slam πŸ‘‘ Triple Crown 🌱 Topic Pioneer ❓ The Questioner (3) ⚑ Prolific Year (11) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (153) πŸš€ Conference Pioneer πŸ’Ž Century Club (112) πŸ”₯ Unstoppable (18)

Conferences

NIPS (53) ICML (24) COLT (12) ICLR (10) AISTATS (8) JMLR (2) AAAI (1) AACL (1) ECCV (1) IJCNLP (1)

Top co-authors

Praneeth Netrapalli (31) Purushottam Kar (13) Inderjit S Dhillon (10) Inderjit S. Dhillon (9) Aditya Kusupati (9) Sewoong Oh (7) Sham Kakade (6) Abhradeep Thakurta (6) Nagarajan Natarajan (6) Ali Farhadi (5)

Research topics

Differential Privacy (6) Core AI (1)

Keywords

stochastic gradient descent (14) sample complexity (12) matrix completion (11) differential privacy (11) online learning (8) non-convex optimization (8) convex optimization (8) representation learning (7) low-rank matrix (7) alternating minimization (7) gradient descent (6) metric learning (6) regret bound (5) multi-label classification (5) hard thresholding (5) sparse recovery (5) principal component analysis (4) collaborative filtering (4) robust regression (4) linear regression (4)

Papers

Masked Generative Nested Transformers with Decode Time Scaling ICML 2025
One-Pass to Reason: Token Duplication and Block-Sparse Mask for Efficient Fine-Tuning on Multi-Turn Reasoning IJCNLP 2025
One-Pass to Reason: Token Duplication and Block-Sparse Mask for Efficient Fine-Tuning on Multi-Turn Reasoning AACL 2025
Matryoshka Quantization ICML 2025
Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts? ICLR 2025
Sample-Efficient Personalization: Modeling User Parameters as Low Rank Plus Sparse Components AISTATS 2024
LookupViT: Compressing visual information to a limited number of tokens ECCV 2024
Time-Reversal Provides Unsupervised Feedback to LLMs NIPS 2024
Mixture of Nested Experts: Adaptive Processing of Visual Tokens NIPS 2024
Dual-Encoders for Extreme Multi-label Classification ICLR 2024
LLM Augmented LLMs: Expanding Capabilities through Composition ICLR 2024
Tandem Transformers for Inference Efficient LLMs ICML 2024
MatFormer: Nested Transformer for Elastic Inference NIPS 2024
Simplicity Bias in 1-Hidden Layer Neural Networks NIPS 2023
Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency NIPS 2023
Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints NIPS 2023
AdANNS: A Framework for Adaptive Semantic Search NIPS 2023
Multi-User Reinforcement Learning with Low Rank Rewards ICML 2023
Multi-Task Differential Privacy Under Distribution Skew ICML 2023
Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks ICLR 2023
Treeformer: Dense Gradient Trees for Efficient Attention Computation ICLR 2023
Online Low Rank Matrix Completion ICLR 2023
Optimal Algorithms for Latent Bandits with Cluster Structure AISTATS 2023
IGLU: Efficient GCN Training via Lazy Updates ICLR 2022
Matryoshka Representation Learning NIPS 2022
Robust Training in High Dimensions via Block Coordinate Geometric Median Descent AISTATS 2022
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs ICLR 2022
S3GC: Scalable Self-Supervised Graph Clustering NIPS 2022
Reproducibility in Optimization: Theoretical Framework and Limits NIPS 2022
DP-PCA: Statistically Optimal and Differentially Private PCA NIPS 2022
(Nearly) Optimal Private Linear Regression for Sub-Gaussian Data via Adaptive Clipping COLT 2022
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates ICML 2021
Do Input Gradients Highlight Discriminative Features? NIPS 2021
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems NIPS 2021
Statistically and Computationally Efficient Linear Meta-representation Learning NIPS 2021
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes NIPS 2021
Differentially Private Model Personalization NIPS 2021
Streaming Linear System Identification with Reverse Experience Replay NIPS 2021
Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization ICML 2021
The Pitfalls of Simplicity Bias in Neural Networks NIPS 2020
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method NIPS 2020
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms NIPS 2020
RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference NIPS 2020
DROCC: Deep Robust One-Class Classification ICML 2020
Optimization and Analysis of the pAp@k Metric for Recommender Systems ICML 2020
Soft Threshold Weight Reparameterization for Learnable Sparsity ICML 2020
Making the Last Iterate of SGD Information Theoretically Optimal COLT 2019
Efficient Algorithms for Smooth Minimax Optimization NIPS 2019
Shallow RNN: Accurate Time-series Classification on Resource Constrained Devices NIPS 2019
Provable Non-linear Inductive Matrix Completion NIPS 2019
Distributional Semantics Meets Multi-Label Learning AAAI 2019
Globally-convergent Iteratively Reweighted Least Squares for Robust Regression Problems AISTATS 2019
Learning Natural Programs from a Few Examples in Real-Time AISTATS 2019
Cost aware Inference for IoT Devices AISTATS 2019
Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression COLT 2019
Open Problem: Do Good Algorithms Necessarily Query Bad Points? COLT 2019
SGD without Replacement: Sharper Rates for General Smooth Convex Functions ICML 2019
Multiple Instance Learning for Efficient Sequential Data Classification on Resource-constrained Devices NIPS 2018
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network NIPS 2018
Differentially Private Matrix Completion Revisited ICML 2018
Accelerating Stochastic Gradient Descent for Least Squares Regression COLT 2018
Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form COLT 2018
Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds NIPS 2018
Parallelizing Stochastic Gradient Descent for Least Squares Regression: Mini-batching, Averaging, and Model Misspecification JMLR 2018
Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples ICLR 2018
On the insufficiency of existing momentum schemes for Stochastic Optimization ICLR 2018
Learning Mixture of Gaussians with Streaming Data NIPS 2017
Thresholding Based Outlier Robust PCA COLT 2017
Consistent Robust Regression NIPS 2017
Global Convergence of Non-Convex Gradient Descent for Computing Matrix Squareroot AISTATS 2017
Recovery Guarantees for One-hidden-layer Neural Networks ICML 2017
ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices ICML 2017
Nearly Optimal Robust Matrix Completion ICML 2017
Active Heteroscedastic Regression ICML 2017
Selective inference for group-sparse linear models NIPS 2016
Regret Bounds for Non-decomposable Metrics with Missing Labels NIPS 2016
Tensor vs. Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations AISTATS 2016
Structured Sparse Regression via Greedy Hard Thresholding NIPS 2016
Mixed Linear Regression with Multiple Components NIPS 2016
Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja’s Algorithm COLT 2016
Surrogate Functions for Maximizing Precision at the Top ICML 2015
Fast Exact Matrix Completion with Finite Samples COLT 2015
Alternating Minimization for Regression Problems with Vector-valued Outputs NIPS 2015
Predtron: A Family of Online Algorithms for General Prediction Problems NIPS 2015
Sparse Local Embeddings for Extreme Multi-label Classification NIPS 2015
Robust Regression via Hard Thresholding NIPS 2015
Optimizing Non-decomposable Performance Measures: A Tale of Two Classes ICML 2015
Learning Mixtures of Discrete Product Distributions using Spectral Decompositions COLT 2014
Learning Sparsely Used Overcomplete Dictionaries COLT 2014
Non-convex Robust PCA NIPS 2014
Provable Submodular Minimization using Wolfe's Algorithm NIPS 2014
(Near) Dimension Independent Risk Bounds for Differentially Private Learning ICML 2014
Large-scale Multi-label Learning with Missing Labels ICML 2014
Universal Matrix Completion ICML 2014
Online and Stochastic Gradient Methods for Non-decomposable Loss Functions NIPS 2014
Provable Tensor Factorization with Missing Data NIPS 2014
On Iterative Hard Thresholding Methods for High-dimensional M-Estimation NIPS 2014
One-Bit Compressed Sensing: Provable Support and Vector Recovery ICML 2013
Phase Retrieval using Alternating Minimization NIPS 2013
Memory Limited, Streaming PCA NIPS 2013
Differentially Private Learning with Kernels ICML 2013
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions ICML 2013
Metric and Kernel Learning Using a Linear Transformation JMLR 2012
Differentially Private Online Learning COLT 2012
Multilabel Classification using Bayesian Compressed Sensing NIPS 2012
Supervised Learning with Similarity Functions NIPS 2012
Orthogonal Matching Pursuit with Replacement NIPS 2011
Similarity-based Learning via Data Driven Embeddings NIPS 2011
Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning NIPS 2010
Inductive Regularized Learning of Kernel Functions NIPS 2010
Guaranteed Rank Minimization via Singular Value Projection NIPS 2010
Matrix Completion from Power-Law Distributed Samples NIPS 2009
Online Metric Learning and Fast Similarity Search NIPS 2008