Algorithms
Foundations of Optimization
Optimization methods are the engine of machine learning algorithms. Examples abound, such as training neural networks with stochastic gradient descent, segmenting images with submodular optimization, or efficiently searching a game tree with bandit algorithms. We…
Counterfactual Multi-Agent Policy Gradients
Many real-world problems, such as network packet routing and the coordination of autonomous vehicles, are naturally modelled as cooperative multi-agent systems. In this talk, I overview some of the key challenges in developing reinforcement learning…
Efficiency Guarantees from Data
Robust Optimization for Non-Convex Objectives
Policy Gradient Methods: Tutorial and New Frontiers
In this tutorial we discuss several recent advances in deep reinforcement learning involving policy gradient methods. These methods have shown significant success in a wide range of domains, including continuous-action domains such as manipulation, locomotion,…
Utilizing Social Media for Disaster Relief
Effective coordination of post-disaster relief operations depends critically on the availability of reliable situational information, as well as on citizen participation in the operations. The advent of online social media (e.g., Twitter, Facebook) and the…
Detection of Aggressive Behaviour on Social Media
As the interaction over the web has increased, incidents of aggression and related events like trolling, cyberbullying, flaming, hate speech, etc. too have increased manifold across the globe. While most of these behaviours like bullying…
Making Voicebots Work for Accents
Voice-driven automated agents such as personal assistants are becoming increasingly popular. However, in a multilingual and multi-cultural country like India, deploying such agents to engage with large sections of the population is highly challenging. A…
