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Ayush Sekhari

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 15, 2026, 1:13 AM AMS

20

papers

682

total citations

papers (20)

Remember What You Want to Forget: Algorithms for Machine Unlearning

NEURIPS 2021arXiv

Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks

NEURIPS 2023arXiv

Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems

NEURIPS 2022arXiv

SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs

NEURIPS 2021arXiv

On the Complexity of Adversarial Decision Making

NEURIPS 2022arXiv

Machine Unlearning Fails to Remove Data Poisoning Attacks

Selective Sampling and Imitation Learning via Online Regression

NEURIPS 2023arXiv

Model-Free Reinforcement Learning with the Decision-Estimation Coefficient

NEURIPS 2023arXiv

Reinforcement Learning with Feedback Graphs

NEURIPS 2020arXiv

Random Latent Exploration for Deep Reinforcement Learning

Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees

GaussMark: A Practical Approach for Structural Watermarking of Language Models

When is Agnostic Reinforcement Learning Statistically Tractable?

NEURIPS 2023arXiv

From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent

NEURIPS 2022arXiv

Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics

The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches

NEURIPS 2025arXiv

System-Aware Unlearning Algorithms: Use Lesser, Forget Faster

Contextual Bandits and Imitation Learning with Preference-Based Active Queries

NEURIPS 2023arXiv

Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations

Neural Active Learning with Performance Guarantees