b'Kai Zhao'

Adaptive Feature Alignment for Adversarial Training

Recent studies reveal that Convolutional Neural Networks (CNNs) are typi...
05/31/2021 ∙ by Tao Wang, et al. ∙ 6 ∙ share

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cuSZ(x): Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs

Error-bounded lossy compression is a critical technique for significantl...
05/27/2021 ∙ by Jiannan Tian, et al. ∙ 0 ∙ share

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Exploring Autoencoder-Based Error-Bounded Compression for Scientific Data

Error-bounded lossy compression is becoming an indispensable technique f...
05/25/2021 ∙ by Jinyang Liu, et al. ∙ 0 ∙ share

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FT-BLAS: A High Performance BLAS Implementation With Online Fault Tolerance

Basic Linear Algebra Subprograms (BLAS) is a core library in scientific ...
04/02/2021 ∙ by Yujia Zhai, et al. ∙ 0 ∙ share

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FakeMix Augmentation Improves Transparent Object Detection

Detecting transparent objects in natural scenes is challenging due to th...
03/24/2021 ∙ by Yang Cao, et al. ∙ 0 ∙ share

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SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors

Efficient error-controlled lossy compressors are becoming critical to th...
01/08/2021 ∙ by Kai Zhao, et al. ∙ 0 ∙ share

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SDC Resilient Error-bounded Lossy Compressor

Lossy compression is one of the most important strategies to resolve the...
10/07/2020 ∙ by Sihuan Li, et al. ∙ 0 ∙ share

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cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data

Error-bounded lossy compression is a state-of-the-art data reduction tec...
07/19/2020 ∙ by Jiannan Tian, et al. ∙ 0 ∙ share

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Dependency Aware Filter Pruning

Convolutional neural networks (CNNs) are typically over-parameterized, b...
05/06/2020 ∙ by Kai Zhao, et al. ∙ 2 ∙ share

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Algorithm-Based Fault Tolerance for Convolutional Neural Networks

Convolutional neural networks (CNNs) are becoming more and more importan...
03/27/2020 ∙ by Kai Zhao, et al. ∙ 0 ∙ share

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Deep Hough Transform for Semantic Line Detection

In this paper, we put forward a simple yet effective method to detect me...
03/10/2020 ∙ by Qi Han, et al. ∙ 14 ∙ share

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Model-Agnostic Structured Sparsification with Learnable Channel Shuffle

Recent advances in convolutional neural networks (CNNs) usually come wit...
02/19/2020 ∙ by Xin-Yu Zhang, et al. ∙ 13 ∙ share

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LinearFold: linear-time approximate RNA folding by 5'-to-3' dynamic programming and beam search

Motivation: Predicting the secondary structure of an RNA sequence is use...
12/22/2019 ∙ by Liang Huang, et al. ∙ 0 ∙ share

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Deep Differentiable Random Forests for Age Estimation

Age estimation from facial images is typically cast as a label distribut...
07/23/2019 ∙ by Wei Shen, et al. ∙ 0 ∙ share

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Translate-to-Recognize Networks for RGB-D Scene Recognition

Cross-modal transfer is helpful to enhance modality-specific discriminat...
04/28/2019 ∙ by Dapeng Du, et al. ∙ 4 ∙ share

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Res2Net: A New Multi-scale Backbone Architecture

Representing features at multiple scales is of great importance for nume...
04/02/2019 ∙ by Shang-Hua Gao, et al. ∙ 0 ∙ share

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When to Finish? Optimal Beam Search for Neural Text Generation (modulo beam size)

In neural text generation such as neural machine translation, summarizat...
08/31/2018 ∙ by Liang Huang, et al. ∙ 0 ∙ share

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Optimizing the F-measure for Threshold-free Salient Object Detection

Current CNN-based solutions to salient object detection (SOD) mainly rel...
05/19/2018 ∙ by Kai Zhao, et al. ∙ 0 ∙ share

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Hi-Fi: Hierarchical Feature Integration for Skeleton Detection

In natural images, skeleton scales (thickness) may significantly vary am...
01/05/2018 ∙ by Kai Zhao, et al. ∙ 0 ∙ share

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Deep Regression Forests for Age Estimation

Age estimation from facial images is typically cast as a nonlinear regre...
12/19/2017 ∙ by Wei Shen, et al. ∙ 0 ∙ share

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OSU Multimodal Machine Translation System Report

This paper describes Oregon State University's submissions to the shared...
10/07/2017 ∙ by Mingbo Ma, et al. ∙ 0 ∙ share

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Jointly Trained Sequential Labeling and Classification by Sparse Attention Neural Networks

Sentence-level classification and sequential labeling are two fundamenta...
09/28/2017 ∙ by Mingbo Ma, et al. ∙ 0 ∙ share

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Joint Syntacto-Discourse Parsing and the Syntacto-Discourse Treebank

Discourse parsing has long been treated as a stand-alone problem indepen...
08/28/2017 ∙ by Kai Zhao, et al. ∙ 0 ∙ share

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Textual Entailment with Structured Attentions and Composition

Deep learning techniques are increasingly popular in the textual entailm...
01/04/2017 ∙ by Kai Zhao, et al. ∙ 0 ∙ share

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DeepSkeleton: Learning Multi-task Scale-associated Deep Side Outputs for Object Skeleton Extraction in Natural Images

Object skeletons are useful for object representation and object detecti...
09/13/2016 ∙ by Wei Shen, et al. ∙ 0 ∙ share

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Urban Pulse: Capturing the Rhythm of Cities

Cities are inherently dynamic. Interesting patterns of behavior typicall...
08/24/2016 ∙ by Fabio Miranda, et al. ∙ 0 ∙ share

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Object Skeleton Extraction in Natural Images by Fusing Scale-associated Deep Side Outputs

Object skeleton is a useful cue for object detection, complementary to t...
03/31/2016 ∙ by Wei Shen, et al. ∙ 0 ∙ share

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Type-Driven Incremental Semantic Parsing with Polymorphism

Semantic parsing has made significant progress, but most current semanti...
11/19/2014 ∙ by Kai Zhao, et al. ∙ 0 ∙ share

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Kai Zhao

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