Papers
4,122 papers found
Inherent Tradeoffs in Learning Fair Representations
Han Zhao, Geoffrey J. Gordon
Innovations Autoencoder and its Application in One-class Anomalous Sequence Detection
Xinyi Wang, Lang Tong
Integral Autoencoder Network for Discretization-Invariant Learning
Yong Zheng Ong, Zuowei Shen, Haizhao Yang
Interlocking Backpropagation: Improving depthwise model-parallelism
Aidan N. Gomez, Oscar Key, Kuba Perlin et al.
Interpolating Predictors in High-Dimensional Factor Regression
Florentina Bunea, Seth Strimas-Mackey, Marten Wegkamp
Interpretable Classification of Categorical Time Series Using the Spectral Envelope and Optimal Scalings
Zeda Li, Scott A. Bruce, Tian Cai
InterpretDL: Explaining Deep Models in PaddlePaddle
Xuhong Li, Haoyi Xiong, Xingjian Li et al.
Interval-censored Hawkes processes
Marian-Andrei Rizoiu, Alexander Soen, Shidi Li et al.
Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning
Sébastien Forestier, Rémy Portelas, Yoan Mollard et al.
Intrinsic Dimension Estimation Using Wasserstein Distance
Adam Block, Zeyu Jia, Yury Polyanskiy et al.
Joint Continuous and Discrete Model Selection via Submodularity
Jonathan Bunton, Paulo Tabuada
Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models
Subhabrata Majumdar, George Michailidis
Joint Inference of Multiple Graphs from Matrix Polynomials
Madeline Navarro, Yuhao Wang, Antonio G. Marques et al.
JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data
Šimon Mandlík, Matěj Račinský, Viliam Lisý et al.
Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence
Mattes Mollenhauer, Stefan Klus, Christof Schütte et al.
Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process Regression with Matérn Correlations
Haoyuan Chen, Liang Ding, Rui Tuo
Kernel Partial Correlation Coefficient --- a Measure of Conditional Dependence
Zhen Huang, Nabarun Deb, Bodhisattva Sen
KL-UCB-Switch: Optimal Regret Bounds for Stochastic Bandits from Both a Distribution-Dependent and a Distribution-Free Viewpoints
Aurélien Garivier, Hédi Hadiji, Pierre Ménard et al.
KoPA: Automated Kronecker Product Approximation
Chencheng Cai, Rong Chen, Han Xiao
Learning from Noisy Pairwise Similarity and Unlabeled Data
Songhua Wu, Tongliang Liu, Bo Han et al.
Learning Green's functions associated with time-dependent partial differential equations
Nicolas Boullé, Seick Kim, Tianyi Shi et al.
Learning linear non-Gaussian directed acyclic graph with diverging number of nodes
Ruixuan Zhao, Xin He, Junhui Wang
Learning Operators with Coupled Attention
Georgios Kissas, Jacob H. Seidman, Leonardo Ferreira Guilhoto et al.