2.7k citations · 4k across the 84 of their papers we have counts for
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Disentangling Dynamics and Content for Control and Planning
Ershad Banijamali, Ahmad Khajenezhad, Ali Ghodsi +1
In this paper, We study the problem of learning a controllable representation for high-dimensional observations of dynamical systems. Specifically, we consider a situation where th…
Robust Locally-Linear Controllable Embedding
Ershad Banijamali, Rui Shu, Mohammad Ghavamzadeh +2
Embed-to-control (E2C) is a model for solving high-dimensional optimal control problems by combining variational auto-encoders with locally-optimal controllers. However, the E2C mo…
Online Learning to Rank in Stochastic Click Models
Masrour Zoghi, Tomas Tunys, Mohammad Ghavamzadeh +3
Online learning to rank is a core problem in information retrieval and machine learning. Many provably efficient algorithms have been recently proposed for this problem in specific…
Active Learning for Accurate Estimation of Linear Models
Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric
We explore the sequential decision making problem where the goal is to estimate uniformly well a number of linear models, given a shared budget of random contexts independently sam…
Model-Independent Online Learning for Influence Maximization
Sharan Vaswani, Branislav Kveton, Zheng Wen +3
We consider influence maximization (IM) in social networks, which is the problem of maximizing the number of users that become aware of a product by selecting a set of "seed" users…