Papers
11,015 papers found
Neural Logic Machines
Honghua Dong, Jiayuan Mao, Tian Lin et al.
Neural network gradient-based learning of black-box function interfaces
Alon Jacovi, Guy Hadash, Einat Kermany et al.
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
Bastian Rieck, Matteo Togninalli, Christian Bock et al.
Neural Probabilistic Motor Primitives for Humanoid Control
Josh Merel, Leonard Hasenclever, Alexandre Galashov et al.
Neural Program Repair by Jointly Learning to Localize and Repair
Marko Vasic, Aditya Kanade, Petros Maniatis et al.
Neural Speed Reading with Structural-Jump-LSTM
Christian Hansen, Casper Hansen, Stephen Alstrup et al.
Neural TTS Stylization with Adversarial and Collaborative Games
Shuang Ma, Daniel Mcduff, Yale Song
Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach
Wenda Zhou, Victor Veitch, Morgane Austern et al.
NOODL: Provable Online Dictionary Learning and Sparse Coding
Sirisha Rambhatla, Xingguo Li, Jarvis Haupt
No Training Required: Exploring Random Encoders for Sentence Classification
John Wieting, Douwe Kiela
Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy
Yuan Xie, Boyi Liu, Qiang Liu et al.
On Computation and Generalization of Generative Adversarial Networks under Spectrum Control
Haoming Jiang, Zhehui Chen, Minshuo Chen et al.
On Self Modulation for Generative Adversarial Networks
Ting Chen, Mario Lucic, Neil Houlsby et al.
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization
Xiangyi Chen, Sijia Liu, Ruoyu Sun et al.
On the loss landscape of a class of deep neural networks with no bad local valleys
Quynh Nguyen, Mahesh Chandra Mukkamala, Matthias Hein
On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data
Nan Lu, Gang Niu, Aditya Krishna Menon et al.
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length
Stanisław Jastrzębski, Zachary Kenton, Nicolas Ballas et al.
On the Sensitivity of Adversarial Robustness to Input Data Distributions
Gavin Weiguang Ding, Kry Yik Chau Lui, Xiaomeng Jin et al.
On the Turing Completeness of Modern Neural Network Architectures
Jorge Pérez, Javier Marinković, Pablo Barceló
On the Universal Approximability and Complexity Bounds of Quantized ReLU Neural Networks
Yukun Ding, Jinglan Liu, Jinjun Xiong et al.
Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams
Mohammad Kachuee, Orpaz Goldstein, Kimmo Kärkkäinen et al.
Optimal Completion Distillation for Sequence Learning
Sara Sabour, William Chan, Mohammad Norouzi
Optimal Control Via Neural Networks: A Convex Approach
Yize Chen, Yuanyuan Shi, Baosen Zhang
Optimal Transport Maps For Distribution Preserving Operations on Latent Spaces of Generative Models
Eirikur Agustsson, Alexander Sage, Radu Timofte et al.