Shuangfei Zhai

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Binghamton University

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Apple Inc.

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Jian Zhang
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Yan Liu
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Yue Wu
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Abhishek Kumar
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Tara Javidi
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Zhongfei Zhang
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Carlos Guestrin
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∙ 12/02/2021

Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models

Modeling the world can benefit robot learning by providing a rich traini...

Nitish Srivastava, et al. ∙

∙ 09/16/2021

Regularized Training of Nearest Neighbor Language Models

Including memory banks in a natural language processing architecture inc...

Jean-Francois Ton, et al. ∙

∙ 07/01/2021

Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks

We analyze the learning dynamics of infinitely wide neural networks with...

Etai Littwin, et al. ∙

∙ 05/28/2021

An Attention Free Transformer

We introduce Attention Free Transformer (AFT), an efficient variant of T...

Shuangfei Zhai, et al. ∙

∙ 05/17/2021

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

Offline Reinforcement Learning promises to learn effective policies from...

Yue Wu, et al. ∙

∙ 04/21/2021

MetricOpt: Learning to Optimize Black-Box Evaluation Metrics

We study the problem of directly optimizing arbitrary non-differentiable...

Chen Huang, et al. ∙

∙ 06/27/2020

On the generalization of learning-based 3D reconstruction

State-of-the-art learning-based monocular 3D reconstruction methods lear...

Miguel Angel Bautista, et al. ∙

∙ 06/18/2020

Set Distribution Networks: a Generative Model for Sets of Images

Images with shared characteristics naturally form sets. For example, in ...

Shuangfei Zhai, et al. ∙

∙ 06/13/2020

Collegial Ensembles

Modern neural network performance typically improves as model size incre...

Etai Littwin, et al. ∙

∙ 10/29/2019

Adversarial Fisher Vectors for Unsupervised Representation Learning

We examine Generative Adversarial Networks (GANs) through the lens of de...

Shuangfei Zhai, et al. ∙

∙ 10/28/2019

Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking

Deep neural networks require collecting and annotating large amounts of ...

Alaaeldin El-Nouby, et al. ∙

∙ 05/15/2019

Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment

In most machine learning training paradigms a fixed, often handcrafted, ...

Chen Huang, et al. ∙

∙ 11/14/2017

A Deep Learning Approach for Expert Identification in Question Answering Communities

In this paper, we describe an effective convolutional neural network fra...

Chen Zheng, et al. ∙

∙ 09/06/2017

Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records

The rapid growth of Electronic Health Records (EHRs), as well as the acc...

Zhengping Che, et al. ∙

∙ 11/26/2016

Structural Correspondence Learning for Cross-lingual Sentiment Classification with One-to-many Mappings

Structural correspondence learning (SCL) is an effective method for cros...

Nana Li, et al. ∙

∙ 11/16/2016

Fully-adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification

Multi-task learning aims to improve generalization performance of multip...

Yongxi Lu, et al. ∙

∙ 11/16/2016

S3Pool: Pooling with Stochastic Spatial Sampling

Feature pooling layers (e.g., max pooling) in convolutional neural netwo...

Shuangfei Zhai, et al. ∙

∙ 05/25/2016

Deep Structured Energy Based Models for Anomaly Detection

In this paper, we attack the anomaly detection problem by directly model...

Shuangfei Zhai, et al. ∙