Papers
Meta Architecture Search
Albert Shaw, Wei Wei, Weiyang Liu et al.
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
Sulaiman Alghunaim, Kun Yuan, Ali H. Sayed
DeepWave: A Recurrent Neural-Network for Real-Time Acoustic Imaging
Matthieu SIMEONI, Sepand Kashani, Paul Hurley et al.
Weight Agnostic Neural Networks
Adam Gaier, David Ha
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents
Alexander Mott, Daniel Zoran, Mike Chrzanowski et al.
Deep Model Transferability from Attribution Maps
Jie Song, Yixin Chen, Xinchao Wang et al.
Envy-Free Classification
Maria-Florina F Balcan, Travis Dick, Ritesh Noothigattu et al.
Efficient Convex Relaxations for Streaming PCA
Raman Arora, Teodor Vanislavov Marinov
Outlier Detection and Robust PCA Using a Convex Measure of Innovation
Mostafa Rahmani, Ping Li
Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations
Kevin Smith, Lingjie Mei, Shunyu Yao et al.
Incremental Few-Shot Learning with Attention Attractor Networks
Mengye Ren, Renjie Liao, Ethan Fetaya et al.
Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples
Tengyu Xu, Shaofeng Zou, Yingbin Liang
Towards Hardware-Aware Tractable Learning of Probabilistic Models
Laura I Galindez Olascoaga, Wannes Meert, Nimish Shah et al.
Copula-like Variational Inference
Marcel Hirt, Petros Dellaportas, Alain Durmus
Weakly Supervised Instance Segmentation using the Bounding Box Tightness Prior
Cheng-Chun Hsu, Kuang-Jui Hsu, Chung-Chi Tsai et al.
Sample-Efficient Deep Reinforcement Learning via Episodic Backward Update
Su Young Lee, Choi Sungik, Sae-Young Chung
Selecting causal brain features with a single conditional independence test per feature
Atalanti Mastakouri, Bernhard Schölkopf, Dominik Janzing
Efficient Deep Approximation of GMMs
Shirin Jalali, Carl Nuzman, Iraj Saniee
Constraint-based Causal Structure Learning with Consistent Separating Sets
Honghao Li, Vincent Cabeli, Nadir Sella et al.
Oracle-Efficient Algorithms for Online Linear Optimization with Bandit Feedback
Shinji Ito, Daisuke Hatano, Hanna Sumita et al.
Thompson Sampling with Information Relaxation Penalties
Seungki Min, Costis Maglaras, Ciamac C. Moallemi
Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting
Jun Shu, Qi Xie, Lixuan Yi et al.
Conditional Structure Generation through Graph Variational Generative Adversarial Nets
Carl Yang, Peiye Zhuang, Wenhan Shi et al.
Gradient based sample selection for online continual learning
Rahaf Aljundi, Min Lin, Baptiste Goujaud et al.
A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation
Mitsuru Kusumoto, Takuya Inoue, Gentaro Watanabe et al.