Aritra Mitra
10 papers · 2021–2026 · 4 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (25) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Bronze 🔥 Unstoppable · Bronze
💎
Century Club · Bronze
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Keyword Collector
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Research topics
Machine Learning
(10)
Optimization & Theory
(8)
Artificial Intelligence
(4)
Mathematics & Optimization
(4)
Reinforcement Learning
(4)
Learning Types
(4)
Optimization
(4)
Methods
(3)
Core AI
(2)
Learning Paradigms
(2)
Deep Learning
(1)
Application Areas
(1)
Applications
(1)
Bayesian & Probabilistic · Artificial Intelligence
(1)
Bayesian & Probabilistic · Machine Learning
(1)
Keywords
sample complexity
(2)
linear quadratic regulator
(2)
finite-time analysis
(2)
adversarial robustness
(2)
temporal difference learning
(2)
multi-agent system
(2)
markov decision process
(1)
policy evaluation
(1)
reinforcement learning
(1)
robust statistics
(1)
distributed optimization
(1)
high-dimensional statistics
(1)
bayesian learning
(1)
learning performance
(1)
stochastic approximation
(1)
markov chain
(1)
linear function approximation
(1)
strong convexity
(1)
policy optimization
(1)
adversarial learning
(1)
Papers
Harnessing Data from Clustered LQR Systems: Personalized and Collaborative Policy Optimization
L4DC 2026
Adversarially-Robust TD Learning with Markovian Data: Finite-Time Rates and Fundamental Limits
AISTATS 2025
Outlier-Robust Linear System Identification Under Heavy-Tailed Noise
L4DC 2025
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
ICLR 2024
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
AISTATS 2024
Towards model-free LQR control over rate-limited channels
L4DC 2024
Linear Stochastic Bandits over a Bit-Constrained Channel
L4DC 2023
Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds
NeurIPS 2022
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients
NeurIPS 2021
Near-Optimal Data Source Selection for Bayesian Learning
L4DC 2021