Papers
iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
Miao Zhang, Steven W. Su, Shirui Pan et al.
Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection
Nadine Chang, Zhiding Yu, Yu-Xiong Wang et al.
Imitation by Predicting Observations
Andrew Jaegle, Yury Sulsky, Arun Ahuja et al.
Implicit Bias of Linear RNNs
Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit et al.
Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold
Kieran A Murphy, Carlos Esteves, Varun Jampani et al.
Implicit rate-constrained optimization of non-decomposable objectives
Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter
Implicit Regularization in Tensor Factorization
Noam Razin, Asaf Maman, Nadav Cohen
Improved Algorithms for Agnostic Pool-based Active Classification
Julian Katz-Samuels, Jifan Zhang, Lalit Jain et al.
Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits
Kwang-Sung Jun, Lalit Jain, Blake Mason et al.
Improved Contrastive Divergence Training of Energy-Based Models
Yilun Du, Shuang Li, Joshua Tenenbaum et al.
Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon Du, Kevin Jamieson
Improved Denoising Diffusion Probabilistic Models
Alexander Quinn Nichol, Prafulla Dhariwal
Improved, Deterministic Smoothing for L_1 Certified Robustness
Alexander J Levine, Soheil Feizi
Improved OOD Generalization via Adversarial Training and Pretraing
Mingyang Yi, Lu Hou, Jiacheng Sun et al.
Improved Regret Bound and Experience Replay in Regularized Policy Iteration
Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori et al.
Improved Regret Bounds of Bilinear Bandits using Action Space Analysis
Kyoungseok Jang, Kwang-Sung Jun, Se-Young Yun et al.
Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range Dependencies.
Denis Lukovnikov, Asja Fischer
Improving Generalization in Meta-learning via Task Augmentation
Huaxiu Yao, Long-Kai Huang, Linjun Zhang et al.
Improving Gradient Regularization using Complex-Valued Neural Networks
Eric C Yeats, Yiran Chen, Hai Li
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
Yangjun Ruan, Karen Ullrich, Daniel S Severo et al.
Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity
Ryan Henderson, Djork-Arné Clevert, Floriane Montanari
Improving Ultrametrics Embeddings Through Coresets
Vincent Cohen-Addad, Rémi De Joannis De Verclos, Guillaume Lagarde
Incentivized Bandit Learning with Self-Reinforcing User Preferences
Tianchen Zhou, Jia Liu, Chaosheng Dong et al.
Incentivizing Compliance with Algorithmic Instruments
Dung Daniel T Ngo, Logan Stapleton, Vasilis Syrgkanis et al.