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Poster
On Transductive Regression
Corinna Cortes · Mehryar Mohri
Author Information
Corinna Cortes (Google Research)
Mehryar Mohri (Google Research & Courant Institute of Mathematical Sciences)
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2023 Poster: Structured Prediction with Stronger Consistency Guarantees »
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2022 Spotlight: Lightning Talks 6A-2 »
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2022 Spotlight: Differentially Private Learning with Margin Guarantees »
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2022 : Invited Talk #1, Differentially Private Learning with Margin Guarantees, Mehryar Mohri »
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2022 Poster: Multi-Class $H$-Consistency Bounds »
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2022 Poster: Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality »
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2022 Poster: Differentially Private Learning with Margin Guarantees »
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2021 Poster: A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning »
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2021 Poster: Learning with User-Level Privacy »
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2021 Poster: Boosting with Multiple Sources »
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2021 Poster: Breaking the centralized barrier for cross-device federated learning »
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2020 Poster: Adapting to Misspecification in Contextual Bandits »
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2020 Poster: Agnostic Learning with Multiple Objectives »
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2020 Poster: Reinforcement Learning with Feedback Graphs »
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2020 Poster: PAC-Bayes Learning Bounds for Sample-Dependent Priors »
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2019 : Mehryar Mohri, "Learning with Sample-Dependent Hypothesis Sets" »
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2019 : Poster Session »
Rishav Chourasia · Yichong Xu · Corinna Cortes · Chien-Yi Chang · Yoshihiro Nagano · So Yeon Min · Benedikt Boecking · Phi Vu Tran · Kamyar Ghasemipour · Qianggang Ding · Shouvik Mani · Vikram Voleti · Rasool Fakoor · Miao Xu · Kenneth Marino · Lisa Lee · Volker Tresp · Jean-Francois Kagy · Marvin Zhang · Barnabas Poczos · Dinesh Khandelwal · Adrien Bardes · Evan Shelhamer · Jiacheng Zhu · Ziming Li · Xiaoyan Li · Dmitrii Krasheninnikov · Ruohan Wang · Mayoore Jaiswal · Emad Barsoum · Suvansh Sanjeev · Theeraphol Wattanavekin · Qizhe Xie · Sifan Wu · Yuki Yoshida · David Kanaa · Sina Khoshfetrat Pakazad · Mehdi Maasoumy -
2019 Poster: Learning GANs and Ensembles Using Discrepancy »
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2019 Poster: Bandits with Feedback Graphs and Switching Costs »
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2019 Poster: Regularized Gradient Boosting »
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2019 Poster: Hypothesis Set Stability and Generalization »
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2018 Poster: Policy Regret in Repeated Games »
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2018 Poster: Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses »
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2018 Poster: Algorithms and Theory for Multiple-Source Adaptation »
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2017 : Mehryar Mohri (NYU) on Tight Learning Bounds for Multi-Class Classification »
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2017 : (Invited Talk) Mehryar Mohri: Regret minimization against strategic buyers. »
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2017 Poster: Discriminative State Space Models »
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2017 Poster: Online Learning with Transductive Regret »
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2017 Poster: Parameter-Free Online Learning via Model Selection »
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2016 Poster: Structured Prediction Theory Based on Factor Graph Complexity »
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2016 Poster: Boosting with Abstention »
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2016 Poster: Optimistic Bandit Convex Optimization »
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2016 Tutorial: Theory and Algorithms for Forecasting Non-Stationary Time Series »
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2015 : A Theory of Multiple Source Adaptation »
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2015 : Learning Theory and Algorithms for Time Series »
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2015 Poster: Revenue Optimization against Strategic Buyers »
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2015 Poster: Learning Theory and Algorithms for Forecasting Non-stationary Time Series »
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2015 Oral: Learning Theory and Algorithms for Forecasting Non-stationary Time Series »
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2014 Workshop: Second Workshop on Transfer and Multi-Task Learning: Theory meets Practice »
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2014 Workshop: NIPS Workshop on Transactional Machine Learning and E-Commerce »
David Parkes · David H Wolpert · Jennifer Wortman Vaughan · Jacob D Abernethy · Amos Storkey · Mark Reid · Ping Jin · Nihar Bhadresh Shah · Mehryar Mohri · Luis E Ortiz · Robin Hanson · Aaron Roth · Satyen Kale · Sebastien Lahaie -
2014 Poster: Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers »
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2014 Poster: Multi-Class Deep Boosting »
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2014 Spotlight: Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers »
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2014 Session: Oral Session 6 »
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2014 Poster: Conditional Swap Regret and Conditional Correlated Equilibrium »
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2013 Poster: Learning Kernels Using Local Rademacher Complexity »
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2013 Spotlight: Learning Kernels Using Local Rademacher Complexity »
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2013 Session: Oral Session 6 »
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2012 Poster: Accuracy at the Top »
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2012 Poster: Spectral Learning of General Weighted Automata via Constrained Matrix Completion »
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2011 Workshop: Domain Adaptation Workshop: Theory and Application »
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2011 Workshop: Sparse Representation and Low-rank Approximation »
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2010 Workshop: Low-rank Methods for Large-scale Machine Learning »
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2010 Poster: Learning Bounds for Importance Weighting »
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2009 Poster: Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models »
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2009 Poster: Polynomial Semantic Indexing »
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2007 Workshop: Efficient Machine Learning - Overcoming Computational Bottlenecks in Machine Learning (Part 1) »
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2007 Poster: Stability Bounds for Non-i.i.d. Processes »
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