闲情居|机器学习领域顶会ICML20精选论文分享(11)
Deep Coordination Graphs Wendelin Boehmer, Vitaly Kurin, Shimon Whiteson
Voice Separation with an Unknown Number of Multiple Speakers Eliya Nachmani, Yossi Adi, Lior Wolf
Predicting Choice with Set-Dependent Aggregation Nir Rosenfeld, Kojin Oshiba, Yaron Singer
Thompson Sampling Algorithms for Mean-Variance Bandits Qiuyu Zhu, Vincent Tan
Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems Hans Kersting, Nicholas Kr?mer, Martin Schiegg, Christian Daniel, Michael Schober, Philipp Hennig
Debiased Sinkhorn barycenters Hicham Janati, Marco Cuturi, Alexandre Gramfort
Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime Stéphane d'Ascoli, Maria Refinetti, Giulio Biroli, Florent Krzakala
Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills Victor Campos, Alexander Trott, Caiming Xiong, Richard Socher, Xavier Giro-i-Nieto, Jordi Torres
Sparsified Linear Programming for Zero-Sum Equilibrium Finding Brian Zhang, Tuomas Sandholm
Extra-gradient with player sampling for faster convergence in n-player games Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna
Entropy Minimization In Emergent Languages Eugene Kharitonov, Rahma Chaabouni, Diane Bouchacourt, Marco Baroni
Spectral Clustering with Graph Neural Networks for Graph Pooling Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi
VFlow: More Expressive Generative Flows with Variational Data Augmentation Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian
Fully Parallel Hyperparameter Search: Reshaped Space-Filling Marie-Liesse Cauwet, Camille Couprie, Julien Dehos, Pauline Luc, Jeremy Rapin, Morgane Riviere, Fabien Teytaud, Olivier Teytaud, Nicolas Usunier
Discount Factor as a Regularizer in Reinforcement Learning Ron Amit, Kamil Ciosek, Ron Meir
On Learning Sets of Symmetric Elements Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin
Learning Similarity Metrics for Numerical Simulations Georg Kohl, Kiwon Um, Nils Thuerey
FR-Train: A mutual information-based approach to fair and robust training Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh
Real-Time Optimisation for Online Learning in Auctions Lorenzo Croissant, Marc Abeille, Clément Calauzènes
Graph Random Neural Features for Distance-Preserving Graph Representations Daniele Zambon, Cesare Alippi, Lorenzo Livi
Modulating Surrogates for Bayesian Optimization Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill Campbell, Carl Henrik Ek
Convolutional Kernel Networks for Graph-Structured Data Dexiong Chen, Laurent Jacob, Julien Mairal
Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking Haoran Sun, Songtao Lu, Mingyi Hong
Proper Network Interpretability Helps Adversarial Robustness in Classification Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, Luca Daniel
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