Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...
For a discrete-time finite-state Markov chain, we develop an adaptive importance sampling scheme to estimate the expected total cost before hitting a set of terminal states. This s...
A Chaitin Omega number is the halting probability of a universal prefix-free Turing machine. Every Omega number is simultaneously computably enumerable (the limit of a computable...
This paper presents Interleaved Stratified Timer Wheels as a novel priority queue data structure for traffic shaping and scheduling in packet-switched networks. The data structure ...