2 citations · 2 across the 2 of their papers we have counts for
4 papers · 1 filter
Offline-to-online hyperparameter transfer for stochastic bandits
Dravyansh Sharma, Arun Sai Suggala
Classic algorithms for stochastic bandits typically use hyperparameters that govern their critical properties such as the trade-off between exploration and exploitation. Tuning the…
CDQuant: Greedy Coordinate Descent for Accurate LLM Quantization
Pranav Ajit Nair, Arun Sai Suggala
Large language models (LLMs) have recently demonstrated remarkable performance across diverse language tasks. But their deployment is often constrained by their substantial computa…
Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization
Ramnath Kumar, Kushal Majmundar, Dheeraj Nagaraj +1
We present Re-weighted Gradient Descent (RGD), a novel optimization technique that improves the performance of deep neural networks through dynamic sample re-weighting. Leveraging…
Second Order Methods for Bandit Optimization and Control
Arun Suggala, Y. Jennifer Sun, Praneeth Netrapalli +1
Bandit convex optimization (BCO) is a general framework for online decision making under uncertainty. While tight regret bounds for general convex losses have been established, exi…