Papers
Improving Robustness of Deep-Learning-Based Image Reconstruction
Ankit Raj, Yoram Bresler, Bo Li
Improving the Gating Mechanism of Recurrent Neural Networks
Albert Gu, Caglar Gulcehre, Thomas Paine et al.
Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking
Haoran Sun, Songtao Lu, Mingyi Hong
Improving Transformer Optimization Through Better Initialization
Xiao Shi Huang, Felipe Perez, Jimmy Ba et al.
Imputer: Sequence Modelling via Imputation and Dynamic Programming
William Chan, Chitwan Saharia, Geoffrey Hinton et al.
Incremental Sampling Without Replacement for Sequence Models
Kensen Shi, David Bieber, Charles Sutton
In Defense of Uniform Convergence: Generalization via Derandomization with an Application to Interpolating Predictors
Jeffrey Negrea, Gintare Karolina Dziugaite, Daniel Roy
Individual Calibration with Randomized Forecasting
Shengjia Zhao, Tengyu Ma, Stefano Ermon
Individual Fairness for k-Clustering
Sepideh Mahabadi, Ali Vakilian
Inducing and Exploiting Activation Sparsity for Fast Inference on Deep Neural Networks
Mark Kurtz, Justin Kopinsky, Rati Gelashvili et al.
Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters
Subho Banerjee, Saurabh Jha, Zbigniew Kalbarczyk et al.
Inductive Relation Prediction by Subgraph Reasoning
Komal Teru, Etienne Denis, Will Hamilton
Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization
Hien Le, Nicolas Gillis, Panagiotis Patrinos
Inexact Tensor Methods with Dynamic Accuracies
Nikita Doikov, Yurii Nesterov
Inferring DQN structure for high-dimensional continuous control
Andrey Sakryukin, Chedy Raissi, Mohan Kankanhalli
Infinite attention: NNGP and NTK for deep attention networks
Jiri Hron, Yasaman Bahri, Jascha Sohl-Dickstein et al.
Influenza Forecasting Framework based on Gaussian Processes
Christoph Zimmer, Reza Yaesoubi
InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs
Zinan Lin, Kiran Thekumparampil, Giulia Fanti et al.
Information Particle Filter Tree: An Online Algorithm for POMDPs with Belief-Based Rewards on Continuous Domains
Johannes Fischer, Ömer Sahin Tas
Information-Theoretic Local Minima Characterization and Regularization
Zhiwei Jia, Hao Su
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
Baifeng Shi, Dinghuai Zhang, Qi Dai et al.
Input-Sparsity Low Rank Approximation in Schatten Norm
Yi Li, David Woodruff
InstaHide: Instance-hiding Schemes for Private Distributed Learning
Yangsibo Huang, Zhao Song, Kai Li et al.
Inter-domain Deep Gaussian Processes
Tim G. J. Rudner, Dino Sejdinovic, Yarin Gal
Interference and Generalization in Temporal Difference Learning
Emmanuel Bengio, Joelle Pineau, Doina Precup