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03/11/2021
Temporal Action Segmentation from Timestamp Supervision
Temporal action segmentation approaches have been very successful recent...
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11/01/2020
On the Distribution of SINR for MIMO Systems with Widely Linear MMSE Receivers
The widely linear least mean square error (WLMMSE) receiver has been an ...
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09/24/2020
Distributed Community Detection for Large Scale Networks Using Stochastic Block Model
With rapid developments of information and technology, large scale netwo...
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08/10/2020
A Full Second-Order Analysis of the Widely Linear MVDR Beamformer for Noncircular Signals
A full performance analysis of the widely linear (WL) minimum variance d...
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07/20/2020
Improving Attention-Based Handwritten Mathematical Expression Recognition with Scale Augmentation and Drop Attention
Handwritten mathematical expression recognition (HMER) is an important r...
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05/18/2020
Joint Multi-Dimension Pruning
We present joint multi-dimension pruning (named as JointPruning), a new ...
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04/06/2020
Robust 3D Self-portraits in Seconds
In this paper, we propose an efficient method for robust 3D self-portrai...
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03/18/2020
PolyFit: Polynomial-based Indexing Approach for Fast Approximate Range Aggregate Queries
Range aggregate queries find frequent application in data analytics. In ...
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03/07/2020
RCC-Dual-GAN: An Efficient Approach for Outlier Detection with Few Identified Anomalies
Outlier detection is an important task in data mining and many technolog...
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03/02/2020
Long Short-Term Sample Distillation
In the past decade, there has been substantial progress at training incr...
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11/11/2019
Learning From Brains How to Regularize Machines
Despite impressive performance on numerous visual tasks, Convolutional N...
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04/12/2019
Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation
Accurate multi-organ abdominal CT segmentation is essential to many clin...
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02/28/2019
CircConv: A Structured Convolution with Low Complexity
Deep neural networks (DNNs), especially deep convolutional neural networ...
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12/12/2018
E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs
Recurrent Neural Networks (RNNs) are becoming increasingly important for...
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09/28/2018
Generative Adversarial Active Learning for Unsupervised Outlier Detection
Outlier detection is an important topic in machine learning and has been...
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08/30/2018
A Unified Analysis of Stochastic Momentum Methods for Deep Learning
Stochastic momentum methods have been widely adopted in training deep ne...
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06/05/2018
EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching
Designing the structure of neural networks is considered one of the most...
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06/03/2018
An Aggressive Genetic Programming Approach for Searching Neural Network Structure Under Computational Constraints
Recently, there emerged revived interests of designing automatic program...
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05/10/2018
Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing
Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendo...
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04/11/2018
Learning Topics using Semantic Locality
The topic modeling discovers the latent topic probability of the given t...
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03/20/2018
Efficient Recurrent Neural Networks using Structured Matrices in FPGAs
Recurrent Neural Networks (RNNs) are becoming increasingly important for...
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03/20/2018
C3PO: Database and Benchmark for Early-stage Malicious Activity Detection in 3D Printing
Increasing malicious users have sought practices to leverage 3D printing...
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03/14/2018
C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs
Recently, significant accuracy improvement has been achieved for acousti...
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02/25/2018
A Framework in CRM Customer Lifecycle: Identify Downward Trend and Potential Issues Detection
Customer retention is one of the primary goals in the area of customer r...
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02/18/2018
Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework
Hardware accelerations of deep learning systems have been extensively in...
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02/15/2018
Image Dataset for Visual Objects Classification in 3D Printing
The rapid development in additive manufacturing (AM), also known as 3D p...
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02/03/2018
An Area and Energy Efficient Design of Domain-Wall Memory-Based Deep Convolutional Neural Networks using Stochastic Computing
With recent trend of wearable devices and Internet of Things (IoTs), it ...
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11/22/2017
Evaluate the Malignancy of Pulmonary Nodules Using the 3D Deep Leaky Noisy-or Network
Automatic diagnosing lung cancer from Computed Tomography (CT) scans inv...
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11/17/2017
Thoracic Disease Identification and Localization with Limited Supervision
Accurate identification and localization of abnormalities from radiology...
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09/09/2017
A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer
In this paper, we present a simple analysis of fast rates with high pr...
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08/29/2017
CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices
Large-scale deep neural networks (DNNs) are both compute and memory inte...
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06/13/2017
SEP-Nets: Small and Effective Pattern Networks
While going deeper has been witnessed to improve the performance of conv...
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03/12/2017
Hardware-Driven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks
Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecede...
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03/01/2017
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Recently low displacement rank (LDR) matrices, or so-called structured m...
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11/18/2016
SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing
With recent advancing of Internet of Things (IoTs), it becomes very attr...
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04/12/2016
Unified Convergence Analysis of Stochastic Momentum Methods for Convex and Non-convex Optimization
Recently, stochastic momentum methods have been widely adopted in train...
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02/06/2016
