1 citations · 1 across the 9 of their papers we have counts for
9 papers
How Accurately Can a Gaussian Approximate Stochastic Approximation Iterates?
Shaan Ul Haque, Zedong Wang, Zixuan Zhang +1
Stochastic approximation (SA) is a method for finding the root of an operator perturbed by noise. The focus of this paper is studying the distribution of SA iterates in finite time…
Fine-Tuning Diffusion Models via Intermediate Distribution Shaping
Gautham Govind Anil, Shaan Ul Haque, Nithish Kannen +3
Diffusion models are widely used for generative tasks across domains. Given a pre-trained diffusion model, it is often desirable to fine-tune it further either to correct for error…
Finite-Time Bounds for Two-Time-Scale Stochastic Approximation with Arbitrary Norm Contractions and Markovian Noise
Siddharth Chandak, Shaan Ul Haque, Nicholas Bambos
Two-time-scale Stochastic Approximation (SA) is an iterative algorithm with applications in reinforcement learning and optimization. Prior finite time analysis of such algorithms h…
A Non-Asymptotic Theory of Seminorm Lyapunov Stability: From Deterministic to Stochastic Iterative Algorithms
Zaiwei Chen, Sheng Zhang, Zhe Zhang +2
We study the problem of solving fixed-point equations for seminorm-contractive operators and establish foundational results on the non-asymptotic behavior of iterative algorithms i…
Stochastic Approximation with Unbounded Markovian Noise: A General-Purpose Theorem
Shaan Ul Haque, Siva Theja Maguluri
Motivated by engineering applications such as resource allocation in networks and inventory systems, we consider average-reward Reinforcement Learning with unbounded state space an…
Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise
Shaan Ul Haque, Sajad Khodadadian, Siva Theja Maguluri
Stochastic approximation (SA) is an iterative algorithm for finding the fixed point of an operator using noisy samples and widely used in optimization and Reinforcement Learning (R…
Concentration bounds for SSP Q-learning for average cost MDPs
Shaan Ul Haque, Vivek Borkar
We derive a concentration bound for a Q-learning algorithm for average cost Markov decision processes based on an equivalent shortest path problem, and compare it numerically with…
Joint Probability Estimation Using Tensor Decomposition and Dictionaries
Shaan ul Haque, Ajit Rajwade, Karthik S. Gurumoorthy
In this work, we study non-parametric estimation of joint probabilities of a given set of discrete and continuous random variables from their (empirically estimated) 2D marginals,…
Learning to Speak on Behalf of a Group: Medium Access Control for Sending a Shared Message
Shaan ul Haque, Siddharth Chandak, Federico Chiariotti +2
The rapid development of Internet of Things (IoT) technologies has not only enabled new applications, but also presented new challenges for reliable communication with limited reso…