Jinjun Xiong

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On Interpretability of Artificial Neural Networks

Deep learning has achieved great successes in many important areas to de...
01/08/2020 ∙ by Fenglei Fan, et al. ∙ 76 ∙ share

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The Design and Implementation of a Scalable DL Benchmarking Platform

The current Deep Learning (DL) landscape is fast-paced and is rife with ...
11/19/2019 ∙ by Cheng Li, et al. ∙ 55 ∙ share

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SkyNet: a Hardware-Efficient Method for Object Detection and Tracking on Embedded Systems

Developing object detection and tracking on resource-constrained embedde...
09/20/2019 ∙ by Xiaofan Zhang, et al. ∙ 41 ∙ share

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NAIS: Neural Architecture and Implementation Search and its Applications in Autonomous Driving

The rapidly growing demands for powerful AI algorithms in many applicati...
11/18/2019 ∙ by Cong Hao, et al. ∙ 24 ∙ share

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DLBricks: Composable Benchmark Generation toReduce Deep Learning Benchmarking Effort on CPUs

The past few years have seen a surge of applying Deep Learning (DL) mode...
11/18/2019 ∙ by Cheng Li, et al. ∙ 23 ∙ share

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SPGNet: Semantic Prediction Guidance for Scene Parsing

Multi-scale context module and single-stage encoder-decoder structure ar...
08/26/2019 ∙ by Bowen Cheng, et al. ∙ 16 ∙ share

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Benanza: Automatic μBenchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs

As Deep Learning (DL) models have been increasingly used in latency-sens...
11/16/2019 ∙ by Cheng Li, et al. ∙ 12 ∙ share

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DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs

The past few years have seen a surge of applying Deep Learning (DL) mode...
11/18/2019 ∙ by Cheng Li, et al. ∙ 11 ∙ share

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TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection

This work provides a simple approach to discover tight object bounding b...
07/13/2018 ∙ by Yunchao Wei, et al. ∙ 10 ∙ share

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Revisiting Pre-training: An Efficient Training Method for Image Classification

The training method of repetitively feeding all samples into a pre-defin...
11/23/2018 ∙ by Bowen Cheng, et al. ∙ 10 ∙ share

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Challenges and Pitfalls of Reproducing Machine Learning Artifacts

An increasingly complex and diverse collection of Machine Learning(ML) m...
04/29/2019 ∙ by Cheng Li, et al. ∙ 6 ∙ share

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Benanza: Automatic uBenchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs

As Deep Learning (DL) models have been increasingly used in latency-sens...
11/16/2019 ∙ by Cheng Li, et al. ∙ 5 ∙ share

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Decoupled Classification Refinement: Hard False Positive Suppression for Object Detection

In this paper, we analyze failure cases of state-of-the-art detectors an...
10/05/2018 ∙ by Bowen Cheng, et al. ∙ 4 ∙ share

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Across-Stack Profiling and Characterization of Machine Learning Models on GPUs

The world sees a proliferation of machine learning/deep learning (ML) mo...
08/19/2019 ∙ by Cheng Li, et al. ∙ 2 ∙ share

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SkyNet: A Champion Model for DAC-SDC on Low Power Object Detection

Developing artificial intelligence (AI) at the edge is always challengin...
06/25/2019 ∙ by Xiaofan Zhang, et al. ∙ 1 ∙ share

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Revisiting RCNN: On Awakening the Classification Power of Faster RCNN

Recent region-based object detectors are usually built with separate cla...
03/19/2018 ∙ by Bowen Cheng, et al. ∙ 0 ∙ share

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Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts

Textual grounding is an important but challenging task for human-compute...
03/29/2018 ∙ by Raymond A. Yeh, et al. ∙ 0 ∙ share

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Face Recognition with Hybrid Efficient Convolution Algorithms on FPGAs

Deep Convolutional Neural Networks have become a Swiss knife in solving ...
03/23/2018 ∙ by Chuanhao Zhuge, et al. ∙ 0 ∙ share

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Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection

Fine-grained action detection is an important task with numerous applica...
11/21/2018 ∙ by Khoi-Nguyen C. Mac, et al. ∙ 0 ∙ share

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MLModelScope: Evaluate and Measure ML Models within AI Pipelines

The current landscape of Machine Learning (ML) and Deep Learning (DL) is...
11/24/2018 ∙ by Abdul Dakkak, et al. ∙ 0 ∙ share

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TrIMS: Transparent and Isolated Model Sharing for Low Latency Deep LearningInference in Function as a Service Environments

Deep neural networks (DNNs) have become core computation components with...
11/24/2018 ∙ by Abdul Dakkak, et al. ∙ 0 ∙ share

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Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era

This report provides an overview of recent work that harnesses the Big D...
02/01/2019 ∙ by Gabrielle Allen, et al. ∙ 0 ∙ share

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Evaluation of Neural Network Uncertainty Estimation with Application to Resource-Constrained Platforms

The ability to accurately estimate uncertainties in neural network predi...
03/05/2019 ∙ by Yukun Ding, et al. ∙ 0 ∙ share

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SCNN: A General Distribution based Statistical Convolutional Neural Network with Application to Video Object Detection

Various convolutional neural networks (CNNs) were developed recently tha...
03/15/2019 ∙ by Tianchen Wang, et al. ∙ 0 ∙ share

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Reinforcement Learning Based Text Style Transfer without Parallel Training Corpus

Text style transfer rephrases a text from a source style (e.g., informal...
03/26/2019 ∙ by Hongyu Gong, et al. ∙ 0 ∙ share

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Document Similarity for Texts of Varying Lengths via Hidden Topics

Measuring similarity between texts is an important task for several appl...
03/26/2019 ∙ by Hongyu Gong, et al. ∙ 0 ∙ share

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FPGA/DNN Co-Design: An Efficient Design Methodology for IoT Intelligence on the Edge

While embedded FPGAs are attractive platforms for DNN acceleration on ed...
04/09/2019 ∙ by Cong Hao, et al. ∙ 0 ∙ share

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A Bi-Directional Co-Design Approach to Enable Deep Learning on IoT Devices

Developing deep learning models for resource-constrained Internet-of-Thi...
05/20/2019 ∙ by Xiaofan Zhang, et al. ∙ 0 ∙ share

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Challenges and Pitfalls of Machine Learning Evaluation and Benchmarking

An increasingly complex and diverse collection of Machine Learning (ML) ...
04/29/2019 ∙ by Cheng Li, et al. ∙ 0 ∙ share

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SCOPE: C3SR Systems Characterization and Benchmarking Framework

This report presents the design of the Scope infrastructure for extensib...
09/18/2018 ∙ by Carl Pearson, et al. ∙ 0 ∙ share

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Accelerating Reduction and Scan Using Tensor Core Units

Driven by deep learning, there has been a surge of specialized processor...
11/24/2018 ∙ by Abdul Dakkak, et al. ∙ 0 ∙ share

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MSU-Net: Multiscale Statistical U-Net for Real-time 3D Cardiac MRI Video Segmentation

Cardiac magnetic resonance imaging (MRI) is an essential tool for MRI-gu...
09/15/2019 ∙ by Tianchen Wang, et al. ∙ 0 ∙ share

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PaRe: A Paper-Reviewer Matching Approach Using a Common Topic Space

Finding the right reviewers to assess the quality of conference submissi...
09/25/2019 ∙ by Omer Anjum, et al. ∙ 0 ∙ share

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Enabling real-time multi-messenger astrophysics discoveries with deep learning

Multi-messenger astrophysics is a fast-growing, interdisciplinary field ...
11/26/2019 ∙ by E. A. Huerta, et al. ∙ 0 ∙ share

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Tensor Recovery from Noisy and Multi-Level Quantized Measurements

Higher-order tensors can represent scores in a rating system, frames in ...
12/05/2019 ∙ by Ren Wang, et al. ∙ 0 ∙ share

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Analysis and Optimization of I/O Cache Coherency Strategies for SoC-FPGA Device

Unlike traditional PCIe-based FPGA accelerators, heterogeneous SoC-FPGA ...
08/04/2019 ∙ by Seung Won Min, et al. ∙ 0 ∙ share

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A Retrospective Recount of Computer Architecture Research with a Data-Driven Study of Over Four Decades of ISCA Publications

This study began with a research project, called DISCvR, conducted at th...
06/22/2019 ∙ by Omer Anjum, et al. ∙ 0 ∙ share

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ELFISH: Resource-Aware Federated Learning on Heterogeneous Edge Devices

In this work, we propose ELFISH - a resource-aware federated learning fr...
12/03/2019 ∙ by Zirui Xu, et al. ∙ 0 ∙ share

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Jinjun Xiong

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