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2006.06979
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Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation
12 June 2020
Masahiro Kato
Takeshi Teshima
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Papers citing
"Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation"
41 / 41 papers shown
Title
Direct Density Ratio Optimization: A Statistically Consistent Approach to Aligning Large Language Models
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Utility Theory of Synthetic Data Generation
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Telescoping Density-Ratio Estimation
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Kai Xu
Michael U. Gutmann
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Rethinking Importance Weighting for Deep Learning under Distribution Shift
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Off-Policy Evaluation and Learning for External Validity under a Covariate Shift
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Masatoshi Uehara
Shota Yasui
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More Efficient Off-Policy Evaluation through Regularized Targeted Learning
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Ivana Malenica
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13 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
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Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
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Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach
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Tianyi Zhang
Gang Niu
Masashi Sugiyama
51
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20 Oct 2019
Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning
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Masatoshi Uehara
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09 Jun 2019
Deep Semi-Supervised Anomaly Detection
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Robert A. Vandermeulen
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Marius Kloft
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06 Jun 2019
Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
Michael Oberst
David Sontag
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14 May 2019
Efficient Counterfactual Learning from Bandit Feedback
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Shota Yasui
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Deep Anomaly Detection Using Geometric Transformations
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Ran El-Yaniv
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28 May 2018
Size-Independent Sample Complexity of Neural Networks
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Ohad Shamir
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Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
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Kashif Rasul
Roland Vollgraf
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Nonparametric regression using deep neural networks with ReLU activation function
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230
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Positive-Unlabeled Learning with Non-Negative Risk Estimator
Ryuichi Kiryo
Gang Niu
M. C. D. Plessis
Masashi Sugiyama
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02 Mar 2017
Policy Learning with Observational Data
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Stefan Wager
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09 Feb 2017
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits
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Alekh Agarwal
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Generative Adversarial Nets from a Density Ratio Estimation Perspective
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Issei Sato
Masahiro Suzuki
Kotaro Nakayama
Y. Matsuo
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10 Oct 2016
Locally Robust Semiparametric Estimation
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J. Escanciano
Hidehiko Ichimura
Whitney Newey
J. M. Robins
89
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29 Jul 2016
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
Sebastian Nowozin
Botond Cseke
Ryota Tomioka
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154
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02 Jun 2016
Wide Residual Networks
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Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning
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External Validity: From Do-Calculus to Transportability Across Populations
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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
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Christian Szegedy
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Adam: A Method for Stochastic Optimization
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Jimmy Ba
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Striving for Simplicity: The All Convolutional Net
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Thomas Brox
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Marginalized Denoising Autoencoders for Domain Adaptation
Minmin Chen
Z. Xu
Kilian Q. Weinberger
Fei Sha
119
818
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18 Jun 2012
Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation
Song Liu
M. Yamada
Nigel Collier
Masashi Sugiyama
60
446
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02 Mar 2012
Doubly Robust Policy Evaluation and Learning
Miroslav Dudík
John Langford
Lihong Li
OffRL
343
697
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23 Mar 2011
f-divergence estimation and two-sample homogeneity test under semiparametric density-ratio models
Takafumi Kanamori
Taiji Suzuki
Masashi Sugiyama
86
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A Contextual-Bandit Approach to Personalized News Article Recommendation
Lihong Li
Wei Chu
John Langford
Robert Schapire
471
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The Offset Tree for Learning with Partial Labels
A. Beygelzimer
John Langford
312
185
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Estimating divergence functionals and the likelihood ratio by convex risk minimization
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Martin J. Wainwright
Michael I. Jordan
225
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Sample Selection Bias Correction Theory
Corinna Cortes
M. Mohri
Michael Riley
Afshin Rostamizadeh
103
350
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Bayesian Online Changepoint Detection
Ryan P. Adams
D. MacKay
245
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