Generalized network tomography. - Gugan Thoppe (Allerton Conference, 2012)

A stochastic Kaczmarz algorithm for network tomography. - Gugan Thoppe; Vivek S. Borkar; D. Manjunath (Autom., 2014)

An Improved Block Coordinate Descent Method for Quadratic Programming in High Dimensions. - Gugan Thoppe; Vivek S. Borkar; Dinesh Garg (CoRR, 2014)

A concentration result for stochastic approximation (Extended abstract). - Gugan Thoppe; Vivek S. Borkar (ITA, 2016)

Concentration Bounds for Two Timescale Stochastic Approximation with Applications to Reinforcement Learning. - Gal Dalal; Balázs Szörényi; Gugan Thoppe; Shie Mannor (CoRR, 2017)

Finite Sample Analysis for TD(0) with Linear Function Approximation. - Gal Dalal; Balázs Szörényi; Gugan Thoppe; Shie Mannor (CoRR, 2017)

Finite Sample Analyses for TD(0) With Function Approximation. - Gal Dalal; Balázs Szörényi; Gugan Thoppe; Shie Mannor (AAAI, 2018)

Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning. - Gal Dalal; Gugan Thoppe; Balázs Szörényi; Shie Mannor (COLT, 2018)

A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound. - Gal Dalal; Balázs Szörényi; Gugan Thoppe (AAAI, 2020)

Change Rate Estimation and Optimal Freshness in Web Page Crawling. - Konstantin Avrachenkov; Kishor Patil; Gugan Thoppe (VALUETOOLS, 2020)

Randomly Weighted d-Complexes: Minimal Spanning Acycles and Persistence Diagrams. - Primoz Skraba; Gugan Thoppe; D. Yogeshwaran (Electron. J. Comb., 2020)

A Law of Iterated Logarithm for Multi-Agent Reinforcement Learning. - Gugan Thoppe; Bhumesh Kumar (NeurIPS, 2021)

Scale Invariant Solutions for Overdetermined Linear Systems with Applications to Reinforcement Learning. - Rahul Madhavan; Gugan Thoppe; Hemanta Makwana (CoRR, 2021)

Does Momentum Help? A Sample Complexity Analysis. - Gugan Thoppe; Rohan Deb; Swetha Ganesh; Amarjit Budhiraja (CoRR, 2021)

Approximate Q-learning and SARSA(0) under the ε-greedy Policy: a Differential Inclusion Analysis. - Aditya Gopalan; Gugan Thoppe (CoRR, 2022)

Online algorithms for estimating change rates of web pages. - Konstantin Avrachenkov; Kishor Patil; Gugan Thoppe (Perform. Evaluation, 2022)

Online Learning with Adversaries: A Differential-Inclusion Analysis. - Swetha Ganesh; Alexandre Reiffers-Masson; Gugan Thoppe (CDC, 2023)

Does Momentum Help in Stochastic Optimization? A Sample Complexity Analysis. - Swetha Ganesh; Rohan Deb; Gugan Thoppe; Amarjit Budhiraja (UAI, 2023)

Improving Sample Efficiency in Evolutionary RL Using Off-Policy Ranking. - Eshwar S. R; Shishir Kolathaya; Gugan Thoppe (VALUETOOLS, 2023)

SoftTreeMax: Exponential Variance Reduction in Policy Gradient via Tree Search. - Gal Dalal; Assaf Hallak; Gugan Thoppe; Shie Mannor; Gal Chechik (CoRR, 2023)

VaR and CVaR Estimation in a Markov Cost Process: Lower and Upper Bounds. - Sanjay Bhat; Prashanth L. A.; Gugan Thoppe (CoRR, 2023)

Reinforcement Learning with Quasi-Hyperbolic Discounting. - S. R. Eshwar; Mayank Motwani; Nibedita Roy; Gugan Thoppe (CDC, 2024)

Federated TD Learning in Heterogeneous Environments with Average Rewards: A Two-timescale Approach with Polyak-Ruppert Averaging. - Ankur Naskar; Gugan Thoppe; Abbasali Koochakzadeh; Vijay Gupta (CDC, 2024)

Towards Optimizing Hyperledger Fabric Performance through Strategic Waiting. - Divya Pulivarthi; S. R. Eshwar; Gugan Thoppe; Kshitij Pratihast; Pavan Sollu; Tittu Varghese; Hrishikesh Nashikkar; Yogesh Simmhan (HIPCW, 2024)

Risk Estimation in a Markov Cost Process: Lower and Upper Bounds. - Gugan Thoppe; Prashanth L. A.; Sanjay P. Bhat (ICML, 2024)

Online Learning of Weakly Coupled MDP Policies for Load Balancing and Auto Scaling. - S. R. Eshwar; Lucas Lopes Felipe; Alexandre Reiffers-Masson; Daniel Sadoc Menasché; Gugan Thoppe (IFIP Networking, 2024)

Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries. - Swetha Ganesh; Jiayu Chen; Gugan Thoppe; Vaneet Aggarwal (Trans. Mach. Learn. Res., 2024)

Reliable Critics: Monotonic Improvement and Convergence Guarantees for Reinforcement Learning. - Eshwar S. R; Gugan Thoppe; Aditya Gopalan; Gal Dalal (CoRR, 2025)

Sequential Attention-based Sampling for Histopathological Analysis. - Tarun G; Naman Malpani; Gugan Thoppe; Sridharan Devarajan (CoRR, 2025)

Parameter-free Optimal Rates for Nonlinear Semi-Norm Contractions with Applications to Q-Learning. - Ankur Naskar; Gugan Thoppe; Vijay Gupta (CoRR, 2025)