
A Deeper Look at the Layerwise Sparsity of Magnitudebased Pruning
Recent discoveries on neural network pruning reveal that, with a careful...
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Learning from Failure: Training Debiased Classifier from Biased Classifier
Neural networks often learn to make predictions that overly rely on spur...
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Guiding Deep Molecular Optimization with Genetic Exploration
De novo molecular design attempts to search over the chemical space for ...
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QOPT: Optimistic Value Function Decentralization for Cooperative MultiAgent Reinforcement Learning
We propose a novel valuebased algorithm for cooperative multiagent rei...
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Learning What to Defer for Maximum Independent Sets
Designing efficient algorithms for combinatorial optimization appears ub...
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Variational Information Distillation for Knowledge Transfer
Transferring knowledge from a teacher neural network pretrained on the s...
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Bucket Renormalization for Approximate Inference
Probabilistic graphical models are a key tool in machine learning applic...
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Gauged MiniBucket Elimination for Approximate Inference
Computing the partition function Z of a discrete graphical model is a fu...
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Gauging Variational Inference
Computing partition function is the most important statistical inference...
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MCMC assisted by Belief Propagaion
Markov Chain Monte Carlo (MCMC) and Belief Propagation (BP) are the most...
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Minimum Weight Perfect Matching via Blossom Belief Propagation
Maxproduct Belief Propagation (BP) is a popular messagepassing algorit...
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Sungsoo Ahn
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