Papers
HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning
Andrey Zhmoginov, Mark Sandler, Maksym Vladymyrov
Identifiability Conditions for Domain Adaptation
Ishaan Gulrajani, Tatsunori Hashimoto
Identification of Linear Non-Gaussian Latent Hierarchical Structure
Feng Xie, Biwei Huang, Zhengming Chen et al.
Identity-Disentangled Adversarial Augmentation for Self-supervised Learning
Kaiwen Yang, Tianyi Zhou, Xinmei Tian et al.
IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data
Tian Gao, Debarun Bhattacharjya, Elliot Nelson et al.
IGLUE: A Benchmark for Transfer Learning across Modalities, Tasks, and Languages
Emanuele Bugliarello, Fangyu Liu, Jonas Pfeiffer et al.
Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging
Anastasios N Angelopoulos, Amit Pal Kohli, Stephen Bates et al.
Imitation Learning by Estimating Expertise of Demonstrators
Mark Beliaev, Andy Shih, Stefano Ermon et al.
Implicit Bias of Linear Equivariant Networks
Hannah Lawrence, Kristian Georgiev, Andrew Dienes et al.
Implicit Bias of the Step Size in Linear Diagonal Neural Networks
Mor Shpigel Nacson, Kavya Ravichandran, Nathan Srebro et al.
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks
Noam Razin, Asaf Maman, Nadav Cohen
Implicit Regularization with Polynomial Growth in Deep Tensor Factorization
Kais Hariz, Hachem Kadri, Stephane Ayache et al.
Importance Weighted Kernel Bayes’ Rule
Liyuan Xu, Yutian Chen, Arnaud Doucet et al.
Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation
Wenxiao Wang, Alexander J Levine, Soheil Feizi
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning
Sattar Vakili, Jonathan Scarlett, Da-Shan Shiu et al.
Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP
Liyu Chen, Rahul Jain, Haipeng Luo
Improved Rates for Differentially Private Stochastic Convex Optimization with Heavy-Tailed Data
Gautam Kamath, Xingtu Liu, Huanyu Zhang
Improved Regret for Differentially Private Exploration in Linear MDP
Dung Daniel T Ngo, Giuseppe Vietri, Steven Wu
Improved StyleGAN-v2 based Inversion for Out-of-Distribution Images
Rakshith Subramanyam, Vivek Narayanaswamy, Mark Naufel et al.
Improve Single-Point Zeroth-Order Optimization Using High-Pass and Low-Pass Filters
Xin Chen, Yujie Tang, Na Li
Improving Adversarial Robustness via Mutual Information Estimation
Dawei Zhou, Nannan Wang, Xinbo Gao et al.
Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation
Giung Nam, Hyungi Lee, Byeongho Heo et al.
Improving Language Models by Retrieving from Trillions of Tokens
Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann et al.
Improving Mini-batch Optimal Transport via Partial Transportation
Khai Nguyen, Dang Nguyen, The-Anh Vu-Le et al.
Improving Out-of-Distribution Robustness via Selective Augmentation
Huaxiu Yao, Yu Wang, Sai Li et al.