Online Learning with Imperfect Hints
Jul 12, 2020
Speakers
Aditya Bhaskara
Speaker · 1 follower
Ashok Cutkosky
Speaker · 1 follower
Ravi Kumar
Speaker · 0 followers
Manish Purohit
Speaker · 0 followers
About
We consider a variant of the classical online linear optimization problem in which at every step, the online player receives a “hint” vector before choosing the action for that round. Rather surprisingly, it was shown that if the hint vector is guaranteed to have a positive correlation with the cost vector, then the online player can achieve a regret of O(log T), thus significantly improving over the O(√(T)) regret in the general setting. However, the result and analysis require the correlation property at all time steps, thus raising the natural question: can we design online learning algorithms that are resilient to bad hints? In this paper we develop algorithms and nearly matching lower bounds for online learning with imperfect hints. Our algorithms are oblivious to the quality of the hints, and the regret bounds interpolate between the always-correlated hints case and the no-hints case. Our results also generalize, simplify, and improve upon previous results on optimistic regret bounds, which can be viewed as an additive version of hints.We consider a variant of the classical online linear optimization problem in which at every step, the online player receives a “hint” vector before choosing the action for that round. Rather surprisingly, it was shown that if the hint vector is guaranteed to have a positive correlation with the cost vector, then the online player can achieve a regret of O(log T), thus significantly improving over the O(√(T)) regret in the general setting. However, the result and analysis require the correlation…
Categories
AI & Data Science
Category · 10.8k presentations
Software & Programming
Category · 1k presentations
About ICML 2020
The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.
Like the format? Trust SlidesLive to capture your next event!
Professional recording and live streaming, delivered globally.
Sharing
Recommended Videos
Presentations on similar topic, category or speaker
Software Engineering Event Modeling using Relative Time in Temporal Knowledge Graphs
Watch later
Graph Convolutional Gaussian Processes for Link Prediction
Watch later
Felix Opolka, …
Stabilizing Bi-Level Hyperparameter Optimization using Moreau-Yosida Regularization
Watch later
Sauptik Dhar, …
Efficient Imitation Learning with Local Trajectory Optimization
Watch later
Jialin Song, …
