Papers
Optimizing Mode Connectivity via Neuron Alignment
Norman Tatro, Pin-Yu Chen, Payel Das et al.
Optimizing Neural Networks via Koopman Operator Theory
Akshunna S. Dogra, William Redman
OrganITE: Optimal transplant donor organ offering using an individual treatment effect
Jeroen Berrevoets, James Jordon, Ioana Bica et al.
Organizing recurrent network dynamics by task-computation to enable continual learning
Lea Duncker, Laura Driscoll, Krishna V. Shenoy et al.
OTLDA: A Geometry-aware Optimal Transport Approach for Topic Modeling
Viet Huynh, He Zhao, Dinh Phung
Outlier Robust Mean Estimation with Subgaussian Rates via Stability
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia
Overfitting Can Be Harmless for Basis Pursuit, But Only to a Degree
Peizhong Ju, Xiaojun Lin, Jia Liu
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality
Yi Zhang, Orestis Plevrakis, Simon S Du et al.
PAC-Bayes Analysis Beyond the Usual Bounds
Omar Rivasplata, Ilja Kuzborskij, Csaba Szepesvari et al.
PAC-Bayesian Bound for the Conditional Value at Risk
Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson
PAC-Bayes Learning Bounds for Sample-Dependent Priors
Pranjal Awasthi, Satyen Kale, Stefani Karp et al.
Parabolic Approximation Line Search for DNNs
Maximus Mutschler, Andreas Zell
Parameterized Explainer for Graph Neural Network
Dongsheng Luo, Wei Cheng, Dongkuan Xu et al.
Parametric Instance Classification for Unsupervised Visual Feature learning
Yue Cao, Zhenda Xie, Bin Liu et al.
Part-dependent Label Noise: Towards Instance-dependent Label Noise
Xiaobo Xia, Tongliang Liu, Bo Han et al.
Partially View-aligned Clustering
Zhenyu Huang, Peng Hu, Joey Tianyi Zhou et al.
Partial Optimal Tranport with applications on Positive-Unlabeled Learning
Laetitia Chapel, Mokhtar Z. Alaya, Gilles Gasso
Passport-aware Normalization for Deep Model Protection
Jie Zhang, Dongdong Chen, Jing Liao et al.
Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning
Shreyas Fadnavis, Joshua Batson, Eleftherios Garyfallidis
Path Integral Based Convolution and Pooling for Graph Neural Networks
Zheng Ma, Junyu Xuan, Yu Guang Wang et al.
Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks
Alexander Shekhovtsov, Viktor Yanush, Boris Flach
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning
Alekh Agarwal, Mikael Henaff, Sham Kakade et al.
Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets
Avetik Karagulyan, Arnak Dalalyan
PEP: Parameter Ensembling by Perturbation
Alireza Mehrtash, Purang Abolmaesumi, Polina Golland et al.
Permute-and-Flip: A new mechanism for differentially private selection
Ryan McKenna, Daniel R. Sheldon