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Ravi Kumar

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

Achievements

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+16 more ↓ 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (18) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (12)
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)

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