Papers
11,951 papers found
Your classifier is secretly an energy based model and you should treat it like one
Will Grathwohl, Kuan-Chieh Wang, Joern-Henrik Jacobsen et al.
A2BCD: Asynchronous Acceleration with Optimal Complexity
Robert Hannah, Fei Feng, Wotao Yin
ACCELERATING NONCONVEX LEARNING VIA REPLICA EXCHANGE LANGEVIN DIFFUSION
Yi Chen, Jinglin Chen, Jing Dong et al.
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks
Charbel Sakr, Naigang Wang, Chia-Yu Chen et al.
A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation
Akhilesh Gotmare, Nitish Shirish Keskar, Caiming Xiong et al.
A Closer Look at Few-shot Classification
Wei-Yu Chen, Yen-Cheng Liu, Zsolt Kira et al.
A comprehensive, application-oriented study of catastrophic forgetting in DNNs
B. Pfülb, A. Gepperth
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks
Sanjeev Arora, Nadav Cohen, Noah Golowich et al.
A Core Method for the Weak Completion Semantics with Skeptical Abduction (Extended Abstract)
Emmanuelle-Anna Dietz Saldanha, Steffen Hölldobler, Carroline Dewi Puspa Kencana Ramli et al.
Acoustic Cues to Topic and Narrow Focus in Egyptian Arabic
Dina El Zarka, Barbara Schuppler, Francesco Cangemi
Active Learning with Partial Feedback
Peiyun Hu, Zachary C. Lipton, Anima Anandkumar et al.
Adaptive Estimators Show Information Compression in Deep Neural Networks
Ivan Chelombiev, Conor Houghton, Cian O'Donnell
Adaptive Gradient Methods with Dynamic Bound of Learning Rate
Liangchen Luo, Yuanhao Xiong, Yan Liu et al.
Adaptive Input Representations for Neural Language Modeling
Alexei Baevski, Michael Auli
Adaptive Posterior Learning: few-shot learning with a surprise-based memory module
Tiago Ramalho, Marta Garnelo
Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization
Guanghui Wang, Shiyin Lu, Lijun Zhang
AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods
Zhiming Zhou*, Qingru Zhang*, Guansong Lu et al.
A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery
Ali Mousavi, Gautam Dasarathy, Richard G. Baraniuk
ADef: an Iterative Algorithm to Construct Adversarial Deformations
Rima Alaifari, Giovanni S. Alberti, Tandri Gauksson
A Direct Approach to Robust Deep Learning Using Adversarial Networks
Huaxia Wang, Chun-Nam Yu
AD-VAT: An Asymmetric Dueling mechanism for learning Visual Active Tracking
Fangwei Zhong, Peng Sun, Wenhan Luo et al.
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
Xuanqing Liu, Yao Li, Chongruo Wu et al.
Adversarial Attacks on Graph Neural Networks via Meta Learning
Daniel Zügner, Stephan Günnemann
Adversarial Audio Synthesis
Chris Donahue, Julian McAuley, Miller Puckette