633 citations · 1.5k across the 68 of their papers we have counts for
7 papers · 1 filter
One-bit feedback is sufficient for upper confidence bound policies
Daniel Vial, Sanjay Shakkottai, R. Srikant
We consider a variant of the traditional multi-armed bandit problem in which each arm is only able to provide one-bit feedback during each pull based on its past history of rewards…
On the Consistency of Maximum Likelihood Estimators for Causal Network Identification
Xiaotian Xie, Dimitrios Katselis, Carolyn L. Beck +1
We consider the problem of identifying parameters of a particular class of Markov chains, called Bernoulli Autoregressive (BAR) processes. The structure of any BAR model is encoded…
Optimal Load Balancing in Bipartite Graphs
Wentao Weng, Xingyu Zhou, R. Srikant
Applications in cloud platforms motivate the study of efficient load balancing under job-server constraints and server heterogeneity. In this paper, we study load balancing on a bi…
The Global Landscape of Neural Networks: An Overview
Ruoyu Sun, Dawei Li, Shiyu Liang +2
One of the major concerns for neural network training is that the non-convexity of the associated loss functions may cause bad landscape. The recent success of neural networks sugg…
Robust Multi-Agent Multi-Armed Bandits
Daniel Vial, Sanjay Shakkottai, R. Srikant
Recent works have shown that agents facing independent instances of a stochastic -armed bandit can collaborate to decrease regret. However, these works assume that each agent al…
Continuous-Time Multi-Armed Bandits with Controlled Restarts
Semih Cayci, Atilla Eryilmaz, R. Srikant
Time-constrained decision processes have been ubiquitous in many fundamental applications in physics, biology and computer science. Recently, restart strategies have gained signifi…