
Parallelizing Contextual Linear Bandits
Standard approaches to decisionmaking under uncertainty focus on sequen...
read it

Towards a DimensionFree Understanding of Adaptive Linear Control
We study the problem of adaptive control of the linear quadratic regulat...
read it

Near Optimal Policy Optimization via REPS
Since its introduction a decade ago, relative entropy policy search (REP...
read it

Regret Bound Balancing and Elimination for Model Selection in Bandits and RL
We propose a simple model selection approach for algorithms in stochasti...
read it

Accelerated Message Passing for EntropyRegularized MAP Inference
Maximum a posteriori (MAP) inference in discretevalued Markov random fi...
read it

Stochastic Bandits with Linear Constraints
We study a constrained contextual linear bandit setting, where the goal ...
read it

Dropout: Explicit Forms and Capacity Control
We investigate the capacity control provided by dropout in various machi...
read it

A Diffusion Process Perspective on Posterior Contraction Rates for Parameters
We show that diffusion processes can be exploited to study the posterior...
read it

Is There an Analog of Nesterov Acceleration for MCMC?
We formulate gradientbased Markov chain Monte Carlo (MCMC) sampling as ...
read it

Rademacher Complexity for Adversarially Robust Generalization
Many machine learning models are vulnerable to adversarial attacks. It h...
read it

Defending Against Saddle Point Attack in ByzantineRobust Distributed Learning
In this paper, we study robust largescale distributed learning in the p...
read it

ByzantineRobust Distributed Learning: Towards Optimal Statistical Rates
In largescale distributed learning, security issues have become increas...
read it

Spectrallynormalized margin bounds for neural networks
This paper presents a marginbased multiclass generalization bound for n...
read it

Convergence of Langevin MCMC in KLdivergence
Langevin diffusion is a commonly used tool for sampling from a given dis...
read it

HorizonIndependent Optimal Prediction with LogLoss in Exponential Families
We study online learning under logarithmic loss with regular parametric ...
read it

AdviceEfficient Prediction with Expert Advice
Adviceefficient prediction with expert advice (in analogy to labeleffi...
read it

Online and Batch Learning Algorithms for Data with Missing Features
We introduce new online and batch algorithms that are robust to data wit...
read it
Peter Bartlett
is this you? claim profile