# Recent Publications

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### Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives

In this paper, we revisit the problem of private stochastic convex optimization. We propose an algorithm based on noisy mirror descent, …

### Corralling Stochastic Bandit Algorithms

We study the problem of corralling stochastic bandit algorithms, that is combining multiple bandit algorithms designed for a stochastic …

### Bandits with Feedback Graphs and Switching Costs

We study the adversarial multi-armed bandit problem where the learner is supplied with partial observations modeled by a feedback graph …

### Efficient Convex Relaxations for Streaming PCA

We revisit two algorithms, matrix stochastic gradient (MSG) and $\ell_2$-regularized MSG (RMSG), that are instances of stochastic …

### Policy Regret in Repeated Games

The notion of policy regret in online learning is a well defined performance measure for the common scenario of adaptive adversaries, …

# Experience

#### Research Intern

May 2020 – Aug 2020
Research intern at Mehryar Mohri’s team, working on upper and lower bounds for certain Reinforcement Learning problems.

#### Johns Hopkins University

Sep 2018 – Dec 2018
Teaching Assistant for Machine Learning: Optimization EN.601.681481

#### Johns Hopkins University

Jan 2018 – May 2018
Teaching Assistant for Machine Learning: Advanced Topics EN.601.779

#### Johns Hopkins University

Jan 2017 – May 2017
Teaching Assistant for Machine Learning EN.601.475

#### IFD Engineering Joint Venture Ltd

Jun 2014 – Sep 2014 Sofia, Bulgaria