Papers
Accelerating Certified Robustness Training via Knowledge Transfer
Pratik Vaishnavi, Kevin Eykholt, Amir Rahmati
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion
Jialun Zhang, Hong-Ming Chiu, Richard Y Zhang
Accelerating Sparse Convolution with Column Vector-Wise Sparsity
Yijun Tan, Kai Han, Kang Zhao et al.
Acceleration in Distributed Sparse Regression
Marie Maros, Gesualdo Scutari
A Characterization of Semi-Supervised Adversarially Robust PAC Learnability
Idan Attias, Steve Hanneke, Yishay Mansour
A Character-Level Length-Control Algorithm for Non-Autoregressive Sentence Summarization
Puyuan Liu, Xiang Zhang, Lili Mou
ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection
HUIPING ZHUANG, Zhenyu Weng, Hongxin Wei et al.
A Classification of $G$-invariant Shallow Neural Networks
Devanshu Agrawal, James Ostrowski
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases
James Harrison, Luke Metz, Jascha Sohl-Dickstein
A Closer Look at Offline RL Agents
Yuwei Fu, Di Wu, Benoit Boulet
A Closer Look at Prototype Classifier for Few-shot Image Classification
Mingcheng Hou, Issei Sato
A Closer Look at the Adversarial Robustness of Deep Equilibrium Models
Zonghan Yang, Tianyu Pang, Yang Liu
A Closer Look at Weakly-Supervised Audio-Visual Source Localization
Shentong Mo, Pedro Morgado
A Combinatorial Perspective on the Optimization of Shallow ReLU Networks
Michael S Matena, Colin A Raffel
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks
Mingrui Liu, Zhenxun Zhuang, Yunwen Lei et al.
A composable machine-learning approach for steady-state simulations on high-resolution grids
Rishikesh Ranade, Chris Hill, Lalit Ghule et al.
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking
Keyu Duan, Zirui Liu, Peihao Wang et al.
A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension
Binh T. Nguyen, Bertrand Thirion, Sylvain Arlot
A Consistent and Differentiable Lp Canonical Calibration Error Estimator
Teodora Popordanoska, Raphael Sayer, Matthew Blaschko
A consistently adaptive trust-region method
Fadi Hamad, Oliver Hinder
A Consolidated Cross-Validation Algorithm for Support Vector Machines via Data Reduction
Boxiang Wang, Archer Yang
A Continuous Time Framework for Discrete Denoising Models
Andrew Campbell, Joe Benton, Valentin De Bortoli et al.
A Contrastive Framework for Neural Text Generation
Yixuan Su, Tian Lan, Yan Wang et al.
A contrastive rule for meta-learning
Nicolas Zucchet, Simon Schug, Johannes von Oswald et al.