← Authors

Ravi Kumar

69 papers · 2008–2025 · 12 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (8) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) πŸƒ Academic Marathon (17) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (12) πŸ—ΊοΈ Taxonomy Completionist (18) 🏠 Conference Loyalist (24) 🀝 Dynamic Duo (35) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ† Grand Slam πŸ”¬ Deep Specialist (22) ❓ The Questioner πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (10) ⚑ Prolific Year (11) πŸ’Ž Century Club (69) πŸ—ƒοΈ Keyword Collector (52)

Conferences

NIPS (24) ICML (18) AISTATS (7) COLT (5) ICLR (4) AAAI (2) ACL (2) EMNLP (2) NAACL (2) AACL (1) ALT (1) IJCNLP (1)

Top co-authors

Badih Ghazi (35) Pasin Manurangsi (32) Pritish Kamath (19) Chiyuan Zhang (16) Manish Purohit (10) Flavio Chierichetti (9) Amer Sinha (7) Andrew Tomkins (7) Yangsibo Huang (6) Ashok Cutkosky (6)

Research topics

Differential Privacy (7) Privacy (1) Statistics (1)

Keywords

differential privacy (20) approximation algorithm (6) regret bound (5) random utility model (4) online linear optimization (3) stochastic gradient descent (3) online algorithm (3) mixture model (3) online learning (3) sample complexity (3) stochastic optimization (3) k-median clustering (2) convex optimization (2) matrix factorization (2) randomized response (2) logarithmic regret (2) logical reasoning (2) stochastic convex optimization (2) privacy-preserving learning (2) deep learning (2)

Papers

LAuReL: Learned Augmented Residual Layer ICML 2025
Scaling Laws for Differentially Private Language Models ICML 2025
Descent with Misaligned Gradients and Applications to Hidden Convexity ICLR 2025
Balls-and-Bins Sampling for DP-SGD AISTATS 2025
Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy ICLR 2025
On Memorization of Large Language Models in Logical Reasoning AACL 2025
PREM: Privately Answering Statistical Queries with Relative Error COLT 2025
On Memorization of Large Language Models in Logical Reasoning IJCNLP 2025
Tight Bounds for Learning RUMs from Small Slates NIPS 2024
How Private are DP-SGD Implementations? ICML 2024
LabelDP-Pro: Learning with Label Differential Privacy via Projections ICLR 2024
Differentially Private Optimization with Sparse Gradients NIPS 2024
On Convex Optimization with Semi-Sensitive Features COLT 2024
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization ICML 2024
Scalable DP-SGD: Shuffling vs. Poisson Subsampling NIPS 2024
Regression with Label Differential Privacy ICLR 2023
On User-Level Private Convex Optimization ICML 2023
Sparsity-Preserving Differentially Private Training of Large Embedding Models NIPS 2023
User-Level Differential Privacy With Few Examples Per User NIPS 2023
On Computing Pairwise Statistics with Local Differential Privacy NIPS 2023
Optimal Unbiased Randomizers for Regression with Label Differential Privacy NIPS 2023
On Differentially Private Sampling from Gaussian and Product Distributions NIPS 2023
Differentially Private Heatmaps AAAI 2023
Bandit Online Linear Optimization with Hints and Queries ICML 2023
Approximating a RUM from Distributions on $k$-Slates AISTATS 2023
Ticketed Learning–Unlearning Schemes COLT 2023
Parsimonious Learning-Augmented Caching ICML 2022
Faster Privacy Accounting via Evolving Discretization ICML 2022
Large-Scale Differentially Private BERT EMNLP 2022
Private Isotonic Regression NIPS 2022
Anonymized Histograms in Intermediate Privacy Models NIPS 2022
Private Rank Aggregation in Central and Local Models AAAI 2022
RUMs from Head-to-Head Contests ICML 2022
Near-tight Closure Bounds for the Littlestone and Threshold Dimensions ALT 2021
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message ICML 2021
On Avoiding the Union Bound When Answering Multiple Differentially Private Queries COLT 2021
Logarithmic Regret from Sublinear Hints NIPS 2021
Online Knapsack with Frequency Predictions NIPS 2021
Locally Private k-Means in One Round ICML 2021
Deep Learning with Label Differential Privacy NIPS 2021
Robust and Private Learning of Halfspaces AISTATS 2021
Power of Hints for Online Learning with Movement Costs AISTATS 2021
Light RUMs ICML 2021
User-Level Differentially Private Learning via Correlated Sampling NIPS 2021
Online Learning with Imperfect Hints ICML 2020
Differentially Private Clustering: Tight Approximation Ratios NIPS 2020
Online Linear Optimization with Many Hints NIPS 2020
Fair Hierarchical Clustering NIPS 2020
Fair Correlation Clustering AISTATS 2020
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead ICML 2020
Faster Algorithms for Binary Matrix Factorization ICML 2019
Efficient Rematerialization for Deep Networks NIPS 2019
Testing Mixtures of Discrete Distributions COLT 2019
Matroids, Matchings, and Fairness AISTATS 2019
Improving Online Algorithms via ML Predictions NIPS 2018
Learning a Mixture of Two Multinomial Logits ICML 2018
Mallows Models for Top-k Lists NIPS 2018
Algorithms for $\ell_p$ Low-Rank Approximation ICML 2017
Fair Clustering Through Fairlets NIPS 2017
Sketching, Embedding and Dimensionality Reduction in Information Theoretic Spaces AISTATS 2016
Conversational Flow in Oxford-style Debates NAACL 2016
On Mixtures of Markov Chains NIPS 2016
Summarization Through Submodularity and Dispersion ACL 2013
Near-Optimal Bounds for Cross-Validation via Loss Stability ICML 2013
Selecting Diverse Features via Spectral Regularization NIPS 2012
Search in the Lost Sense of β€œQuery”: Question Formulation in Web Search Queries and its Temporal Changes ACL 2011
Matching Reviews to Objects using a Language Model EMNLP 2009
For a few dollars less: Identifying review pages sans human labels NAACL 2009
Mortal Multi-Armed Bandits NIPS 2008