Papers
11,951 papers found
Divide-and-Conquer Reinforcement Learning
Dibya Ghosh, Avi Singh, Aravind Rajeswaran et al.
Do GANs learn the distribution? Some Theory and Empirics
Sanjeev Arora, Andrej Risteski, Yi Zhang
Don't Decay the Learning Rate, Increase the Batch Size
Samuel L. Smith, Pieter-Jan Kindermans, Chris Ying et al.
DORA The Explorer: Directed Outreaching Reinforcement Action-Selection
Lior Fox, Leshem Choshen, Yonatan Loewenstein
Dual-Speed MR Safe Pneumatic Stepper Motors
Vincent Groenhuis, Françoise Siepel, Stefano Stramigioli
Dynamic Neural Program Embeddings for Program Repair
Ke Wang, Rishabh Singh, Zhendong Su
Efficient Pruning of Large Knowledge Graphs
Stefano Faralli, Irene Finocchi, Simone Paolo Ponzetto et al.
Efficient Sparse-Winograd Convolutional Neural Networks
Xingyu Liu, Jeff Pool, Song Han et al.
Eigenoption Discovery through the Deep Successor Representation
Marlos C. Machado, Clemens Rosenbaum, Xiaoxiao Guo et al.
Emergence of grid-like representations by training recurrent neural networks to perform spatial localization
Christopher J. Cueva, Xue-Xin Wei
Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input
Angeliki Lazaridou, Karl Moritz Hermann, Karl Tuyls et al.
Emergent Communication in a Multi-Modal, Multi-Step Referential Game
Katrina Evtimova, Andrew Drozdov, Douwe Kiela et al.
Emergent Communication through Negotiation
Kris Cao, Angeliki Lazaridou, Marc Lanctot et al.
Emergent Complexity via Multi-Agent Competition
Trapit Bansal, Jakub Pachocki, Szymon Sidor et al.
Emergent Translation in Multi-Agent Communication
Jason Lee, Kyunghyun Cho, Jason Weston et al.
Emotional Prosody Perception in Mandarin-speaking Congenital Amusics
Yixin Zhang, Tianzhu Geng, Jinsong Zhang
Empirical Risk Landscape Analysis for Understanding Deep Neural Networks
Pan Zhou, Jiashi Feng
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
Shiyu Liang, Yixuan Li, R. Srikant
Ensemble Adversarial Training: Attacks and Defenses
Florian Tramèr, Alexey Kurakin, Nicolas Papernot et al.
Espresso: Efficient Forward Propagation for Binary Deep Neural Networks
Fabrizio Pedersoli, George Tzanetakis, Andrea Tagliasacchi
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
Tsui-Wei Weng*, Huan Zhang*, Pin-Yu Chen et al.
Event Factuality Identification via Generative Adversarial Networks with Auxiliary Classification
Zhong Qian, Peifeng Li, Yue Zhang et al.
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering
Shuohang Wang, Mo Yu, Jing Jiang et al.
Evolving AI from Research to Real Life – Some Challenges and Suggestions
Sandya Mannarswamy, Shourya Roy
Expressive power of recurrent neural networks
Valentin Khrulkov, Alexander Novikov, Ivan Oseledets