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IronMan: GNN-assisted Design Space Exploration in High-Level Synthesis via Reinforcement Learning
Despite the great success of High-Level Synthesis (HLS) tools, we observ...
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A Survey of Machine Learning for Computer Architecture and Systems
It has been a long time that computer architecture and systems are optim...
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Boundary-Aware Geometric Encoding for Semantic Segmentation of Point Clouds
Boundary information plays a significant role in 2D image segmentation, ...
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AU-Expression Knowledge Constrained Representation Learning for Facial Expression Recognition
Recognizing human emotion/expressions automatically is quite an expected...
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Training and Inference for Integer-Based Semantic Segmentation Network
Semantic segmentation has been a major topic in research and industry in...
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Rubik: A Hierarchical Architecture for Efficient Graph Learning
Graph convolutional network (GCN) emerges as a promising direction to le...
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SEALing Neural Network Models in Secure Deep Learning Accelerators
Deep learning (DL) accelerators are increasingly deployed on edge device...
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Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition
Data inconsistency and bias are inevitable among different facial expres...
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Brain Tumor Anomaly Detection via Latent Regularized Adversarial Network
With the development of medical imaging technology, medical images have ...
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GNNAdvisor: An Efficient Runtime System for GNN Acceleration on GPUs
As the emerging trend of the graph-based deep learning, Graph Neural Net...
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SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation
We present SmartExchange, an algorithm-hardware co-design framework to t...
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NTIRE 2020 Challenge on Image Demoireing: Methods and Results
This paper reviews the Challenge on Image Demoireing that was part of th...
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TIMELY: Pushing Data Movements and Interfaces in PIM Accelerators Towards Local and in Time Domain
Resistive-random-access-memory (ReRAM) based processing-in-memory (R^2PI...
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Comparing SNNs and RNNs on Neuromorphic Vision Datasets: Similarities and Differences
Neuromorphic data, recording frameless spike events, have attracted cons...
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Computation on Sparse Neural Networks: an Inspiration for Future Hardware
Neural network models are widely used in solving many challenging proble...
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Meta Segmentation Network for Ultra-Resolution Medical Images
Despite recent progress on semantic segmentation, there still exist huge...
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Anomaly Detection by Latent Regularized Dual Adversarial Networks
Anomaly detection is a fundamental problem in computer vision area with ...
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Acoustic anomaly detection via latent regularized gaussian mixture generative adversarial networks
Acoustic anomaly detection aims at distinguishing abnormal acoustic sign...
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Novelty Detection via Non-Adversarial Generative Network
One-class novelty detection is the process of determining if a query exa...
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Characterizing and Understanding GCNs on GPU
Graph convolutional neural networks (GCNs) have achieved state-of-the-ar...
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SceneEncoder: Scene-Aware Semantic Segmentation of Point Clouds with A Learnable Scene Descriptor
Besides local features, global information plays an essential role in se...
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Memristor Hardware-Friendly Reinforcement Learning
Recently, significant progress has been made in solving sophisticated pr...
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HyGCN: A GCN Accelerator with Hybrid Architecture
In this work, we first characterize the hybrid execution patterns of GCN...
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Exploring Adversarial Attack in Spiking Neural Networks with Spike-Compatible Gradient
Recently, backpropagation through time inspired learning algorithms are ...
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A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural Networks
In recent years, plenty of metrics have been proposed to identify networ...
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Poq: Projection-based Runtime Assertions for Debugging on a Quantum Computer
In this paper, we propose Poq, a runtime assertion scheme for debugging ...
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DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks
The rapidly growing parameter volume of deep neural networks (DNNs) hind...
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Comprehensive SNN Compression Using ADMM Optimization and Activity Regularization
Spiking neural network is an important family of models to emulate the b...
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Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers
Deep neural network (DNN) quantization converting floating-point (FP) da...
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AccD: A Compiler-based Framework for Accelerating Distance-related Algorithms on CPU-FPGA Platforms
As a promising solution to boost the performance of distance-related alg...
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Semi-Supervised Video Salient Object Detection Using Pseudo-Labels
Deep learning-based video salient object detection has recently achieved...
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Neural Network Model Extraction Attacks in Edge Devices by Hearing Architectural Hints
As neural networks continue their reach into nearly every aspect of soft...
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FPSA: A Full System Stack Solution for Reconfigurable ReRAM-based NN Accelerator Architecture
Neural Network (NN) accelerators with emerging ReRAM (resistive random a...
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QGAN: Quantized Generative Adversarial Networks
The intensive computation and memory requirements of generative adversar...
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A Secure and Persistent Memory System for Non-volatile Memory
In the non-volatile memory, ensuring the security and correctness of per...
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Facial Landmark Machines: A Backbone-Branches Architecture with Progressive Representation Learning
Facial landmark localization plays a critical role in face recognition a...
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Bi-GANs-ST for Perceptual Image Super-resolution
Image quality measurement is a critical problem for image super-resoluti...
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Batch Normalization Sampling
Deep Neural Networks (DNNs) thrive in recent years in which Batch Normal...
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Dynamic Sparse Graph for Efficient Deep Learning
We propose to execute deep neural networks (DNNs) with dynamic and spars...
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In-memory multiplication engine with SOT-MRAM based stochastic computing
Processing-in-memory (PIM) turns out to be a promising solution to break...
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Deep Multi-View Clustering via Multiple Embedding
Exploring the information among multiple views usually leads to more pro...
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Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy
When learning from a batch of logged bandit feedback, the discrepancy be...
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Crossbar-aware neural network pruning
Crossbar architecture based devices have been widely adopted in neural n...
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Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training
Exploiting sparsity enables hardware systems to run neural networks fast...
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Weakly Supervised Salient Object Detection Using Image Labels
Deep learning based salient object detection has recently achieved great...
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L1-Norm Batch Normalization for Efficient Training of Deep Neural Networks
Batch Normalization (BN) has been proven to be quite effective at accele...
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PIRT: A Runtime Framework to Enable Energy-Efficient Real-Time Robotic Applications on Heterogeneous Architectures
Enabling full robotic workloads with diverse behaviors on mobile systems...
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Bridging the Gap Between Neural Networks and Neuromorphic Hardware with A Neural Network Compiler
Different from training common neural networks (NNs) for inference on ge...
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Effective Image Retrieval via Multilinear Multi-index Fusion
Multi-index fusion has demonstrated impressive performances in retrieval...
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Robust Kernelized Multi-View Self-Representations for Clustering by Tensor Multi-Rank Minimization
Most recently, tensor-SVD is implemented on multi-view self-representati...
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