Ness Shroff
28 papers · 2017–2025 · 5 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (10) π Interdisciplinary Bridge π Conference Polyglot (5)
π
Conference Polyglot
(5)
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Academic Marathon
(8)
π§
Keyword Pioneer
π
Keyword Champion
(2)
π€
Dynamic Duo
(10)
π
Triple Crown
ποΈ
Keyword Collector
(83)
β
The Questioner
β‘
Prolific Year
(6)
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Century Club
(28)
π₯
Unstoppable
(9)
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Trend Setter
Conferences
ICLR (9)
ICML (8)
NIPS (6)
AISTATS (4)
IJCAI (1)
Top co-authors
Keywords
regret bound
(7)
sample complexity
(3)
stochastic optimization
(2)
upper confidence bound
(2)
non-stationary environment
(2)
generalization error
(2)
linear function approximation
(2)
neural tangent kernel
(2)
online learning
(2)
active learning
(2)
learning theory
(2)
model-free reinforcement learning
(2)
coded computation
(2)
gradient descent
(2)
constrained markov decision process
(2)
sublinear regret
(2)
constrained reinforcement learning
(1)
convex optimization
(1)
catastrophic forgetting
(1)
policy optimization
(1)
Papers
Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach
ICLR 2025
How to Find the Exact Pareto Front for Multi-Objective MDPs?
ICLR 2025
Unlocking the Power of Rehearsal in Continual Learning: A Theoretical Perspective
ICML 2025
Provably Efficient RL for Linear MDPs under Instantaneous Safety Constraints in Non-Convex Feature Spaces
ICML 2025
Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers
ICLR 2025
Theory on Mixture-of-Experts in Continual Learning
ICLR 2025
Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning
ICLR 2024
Towards Achieving Sub-linear Regret and Hard Constraint Violation in Model-free RL
AISTATS 2024
Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping
ICLR 2024
A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints
ICML 2023
Non-Convex Bilevel Optimization with Time-Varying Objective Functions
NIPS 2023
Provably Efficient Model-Free Algorithms for Non-stationary CMDPs
AISTATS 2023
Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning
ICLR 2023
Achieving Sub-linear Regret in Infinite Horizon Average Reward Constrained MDP with Linear Function Approximation
ICLR 2023
Near-Optimal Adversarial Reinforcement Learning with Switching Costs
ICLR 2023
Theory on Forgetting and Generalization of Continual Learning
ICML 2023
Weighted Gaussian Process Bandits for Non-stationary Environments
AISTATS 2022
On the Generalization Power of the Overfitted Three-Layer Neural Tangent Kernel Model
NIPS 2022
Provably Efficient Model-Free Constrained RL with Linear Function Approximation
NIPS 2022
On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models
ICML 2021
Sample Complexity Bounds for Active Ranking from Multi-wise Comparisons
NIPS 2021
The Sample Complexity of Best-$k$ Items Selection from Pairwise Comparisons
ICML 2020
Data Poisoning Attacks on Stochastic Bandits
ICML 2019
On Sample Complexity Upper and Lower Bounds for Exact Ranking from Noisy Comparisons
NIPS 2019
Computation Efficient Coded Linear Transform
AISTATS 2019
UCBoost: A Boosting Approach to Tame Complexity and Optimality for Stochastic Bandits
IJCAI 2018
Coded Sparse Matrix Multiplication
ICML 2018
A New Alternating Direction Method for Linear Programming
NIPS 2017