Search Results for author: Anqi Liu

Found 21 papers, 4 papers with code

Scaling Fair Learning to Hundreds of Intersectional Groups

no code implementations29 Sep 2021 Eric Zhao, De-An Huang, Hao liu, Zhiding Yu, Anqi Liu, Olga Russakovsky, Anima Anandkumar

In real-world applications, however, there are multiple protected attributes yielding a large number of intersectional protected groups.

Fairness Knowledge Distillation

Dynamic Social Media Monitoring for Fast-Evolving Online Discussions

no code implementations24 Feb 2021 Maya Srikanth, Anqi Liu, Nicholas Adams-Cohen, Jian Cao, R. Michael Alvarez, Anima Anandkumar

However, collecting social media data using a static set of keywords fails to satisfy the growing need to monitor dynamic conversations and to study fast-changing topics.

Decision Making Time Series

Robust Fairness under Covariate Shift

1 code implementation11 Oct 2020 Ashkan Rezaei, Anqi Liu, Omid Memarrast, Brian Ziebart

We investigate fairness under covariate shift, a relaxation of the iid assumption in which the inputs or covariates change while the conditional label distribution remains the same.

Fairness

Distributionally Robust Learning for Uncertainty Calibration under Domain Shift

no code implementations8 Oct 2020 Haoxuan Wang, Anqi Liu, Zhiding Yu, Junchi Yan, Yisong Yue, Anima Anandkumar

We detect such domain shifts through the use of a binary domain classifier and integrate it with the task network and train them jointly end-to-end.

Density Ratio Estimation Unsupervised Domain Adaptation

Distributionally Robust Learning for Unsupervised Domain Adaptation

no code implementations28 Sep 2020 Haoxuan Wang, Anqi Liu, Zhiding Yu, Yisong Yue, Anima Anandkumar

This formulation motivates the use of two neural networks that are jointly trained --- a discriminative network between the source and target domains for density-ratio estimation, in addition to the standard classification network.

Density Ratio Estimation Unsupervised Domain Adaptation

Active Learning under Label Shift

no code implementations16 Jul 2020 Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue

We address the problem of active learning under label shift: when the class proportions of source and target domains differ.

Active Learning

Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems

no code implementations9 May 2020 Yashwanth Kumar Nakka, Anqi Liu, Guanya Shi, Anima Anandkumar, Yisong Yue, Soon-Jo Chung

The Info-SNOC algorithm is used to compute a sub-optimal pool of safe motion plans that aid in exploration for learning unknown residual dynamics under safety constraints.

Motion Planning Optimal Motion Planning +1

Triply Robust Off-Policy Evaluation

no code implementations13 Nov 2019 Anqi Liu, Hao liu, Anima Anandkumar, Yisong Yue

Ours is a general approach that can be used to augment any existing OPE method that utilizes the direct method.

Multi-Armed Bandits

Robust Regression for Safe Exploration in Control

no code implementations L4DC 2020 Anqi Liu, Guanya Shi, Soon-Jo Chung, Anima Anandkumar, Yisong Yue

To address this challenge, we present a deep robust regression model that is trained to directly predict the uncertainty bounds for safe exploration.

Generalization Bounds Safe Exploration

Modeling and Interpreting Real-world Human Risk Decision Making with Inverse Reinforcement Learning

no code implementations13 Jun 2019 Quanying Liu, Haiyan Wu, Anqi Liu

Our results demonstrate that IRL is an effective tool to model human decision-making behavior, as well as to help interpret the human psychological process in risk decision-making.

Decision Making reinforcement-learning

Regularized Learning for Domain Adaptation under Label Shifts

2 code implementations ICLR 2019 Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar

We derive a generalization bound for the classifier on the target domain which is independent of the (ambient) data dimensions, and instead only depends on the complexity of the function class.

Domain Adaptation

Learning Gibbs-regularized GANs with variational discriminator reparameterization

no code implementations27 Sep 2018 Nicholas Rhinehart, Anqi Liu, Kihyuk Sohn, Paul Vernaza

We propose a novel approach to regularizing generative adversarial networks (GANs) leveraging learned {\em structured Gibbs distributions}.

Trajectory Forecasting

Kernel Robust Bias-Aware Prediction under Covariate Shift

no code implementations28 Dec 2017 Anqi Liu, Rizal Fathony, Brian D. Ziebart

Robust Bias-Aware (RBA) prediction provides the conditional label distribution that is robust to the worstcase logarithmic loss for the target distribution while matching feature expectation constraints from the source distribution.

Robust Covariate Shift Prediction with General Losses and Feature Views

no code implementations28 Dec 2017 Anqi Liu, Brian D. Ziebart

Covariate shift relaxes the widely-employed independent and identically distributed (IID) assumption by allowing different training and testing input distributions.

Adversarial Multiclass Classification: A Risk Minimization Perspective

no code implementations NeurIPS 2016 Rizal Fathony, Anqi Liu, Kaiser Asif, Brian Ziebart

Recently proposed adversarial classification methods have shown promising results for cost sensitive and multivariate losses.

Classification General Classification

Etude acoustique et repr\'esentation phonologique sur /ə˞/ suffixe rhotique en mandarin (Acoustic study and phonological representation of the rhotic suffix /ə˞/ in mandarin)

no code implementations JEPTALNRECITAL 2016 Anqi Liu

Historiquement, le suffixe /ə˞/ est un suffixe diminutif correspondant au mot 儿 ({\textless}er{\textgreater} en pinyin) qui signifie {''}petitesse{''}.

Robust Classification Under Sample Selection Bias

no code implementations NeurIPS 2014 Anqi Liu, Brian Ziebart

In many important machine learning applications, the source distribution used to estimate a probabilistic classifier differs from the target distribution on which the classifier will be used to make predictions.

Classification General Classification +2

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