Algorithms
Deep Policy Gradient Algorithms: A Closer Look
Deep reinforcement learning methods are behind some of the most publicized recent results in machine learning. In spite of these successes, however, deep RL methods face a number of systemic issues: brittleness to small changes…
Active Ranking with Subset-wise Preferences
Efficient Algorithms for High Dimensional Robust Learning
We study high-dimensional estimation in a setting where an adversary is allowed to arbitrarily corrupt an $\varepsilon$-fraction of the samples. Such questions have a rich history spanning statistics, machine learning and theoretical computer science. Even…
Machine Learning Systems for Highly Distributed and Rapidly Growing Data
The usability and practicality of machine learning are largely influenced by two critical factors: low latency and low cost. However, achieving low latency and low cost is very challenging when machine learning depends on real-world…
Get Your Data Together! Algorithms for Managing Data Lakes
Data lakes (e.g., enterprise data catalogs and Open Data portals) are data dumps if users cannot find and utilize the data in them. In this talk, I present two problems in massive, dynamic data lakes:…
