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Showing papers from Indian Institute of Technology, Hyderabad Show all papers

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A Refined Sample-Complexity Analysis of Robust Policy Optimization under Decaying Actor Stepsizes

Swetha Ganesh, Vaneet Aggarwal

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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88%Must read
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Breaking the Bias Barrier in Concave Multi-Objective Reinforcement Learning

Concave scalarized multi-objective RL suffers biased gradients that cause O(ε⁻⁴) sample complexity; multi-level Monte Carlo NPG achieves optimal O(ε⁻²).

Swetha Ganesh, Jason Chia, Vaneet Aggarwal

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 4/5
72%Highly rated
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Adversary-Robust Learning from Fully Asynchronous Directional Derivative Estimates

FAR-SIGN enables adversary-resilient fully asynchronous parameter-server optimization via signed directional updates with two-timescale bias correction, achieving near-optimal convergence rates for nonconvex objectives.

Anik Kumar Paul, Nibedita Roy, Nagesh Talagani, Swetha Ganesh and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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8/20 AI panelreviewers recommend it

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AI panel: 8 of 20 reviewers recommend it
lenient 3/5
medium 4/10
strict 1/5