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PredCoin: Defense against Query-based Hard-label Attack
Many adversarial attacks and defenses have recently been proposed for De...
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On Provable Backdoor Defense in Collaborative Learning
As collaborative learning allows joint training of a model using multipl...
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Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning
As power systems are undergoing a significant transformation with more u...
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Hermes: Decentralized Dynamic Spectrum Access System for Massive Devices Deployment in 5G
With the incoming 5G network, the ubiquitous Internet of Things (IoT) de...
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Fast and Scalable Sparse Triangular Solver for Multi-GPU Based HPC Architectures
Designing efficient and scalable sparse linear algebra kernels on modern...
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Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective
Federated learning (FL) is a popular distributed learning framework that...
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GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs
Graph-based semi-supervised node classification (GraphSSC) has wide appl...
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ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing
The next generation HPC and data centers are likely to be reconfigurable...
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Towards Latency-aware DNN Optimization with GPU Runtime Analysis and Tail Effect Elimination
Despite the superb performance of State-Of-The-Art (SOTA) DNNs, the incr...
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A Bayesian Approach for Characterizing and Mitigating Gate and Measurement Errors
Various noise models have been developed in quantum computing study to d...
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The Effectiveness of Memory Replay in Large Scale Continual Learning
We study continual learning in the large scale setting where tasks in th...
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Evasion Attacks to Graph Neural Networks via Influence Function
Graph neural networks (GNNs) have achieved state-of-the-art performance ...
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Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs
Link prediction in dynamic graphs (LPDG) is an important research proble...
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LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets
Federated learning is a popular distributed machine learning paradigm wi...
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1-Bit Massive MIMO Transmission: Embracing Interference with Symbol-Level Precoding
The deployment of large-scale antenna arrays for cellular base stations ...
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Accelerating Binarized Neural Networks via Bit-Tensor-Cores in Turing GPUs
Despite foreseeing tremendous speedups over conventional deep neural net...
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Symbol-Level Precoding Made Practical for Multi-Level Modulations via Block-Level Rescaling
In this letter, we propose an interference exploitation symbol-level pre...
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SOLA: Continual Learning with Second-Order Loss Approximation
Neural networks have achieved remarkable success in many cognitive tasks...
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Learning to Incentivize Other Learning Agents
The challenge of developing powerful and general Reinforcement Learning ...
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Visual Localization Using Semantic Segmentation and Depth Prediction
In this paper, we propose a monocular visual localization pipeline lever...
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PoliteCamera: Respecting Strangers' Privacy in Mobile Photographing
Camera is a standard on-board sensor of modern mobile phones. It makes p...
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MVStylizer: An Efficient Edge-Assisted Video Photorealistic Style Transfer System for Mobile Phones
Recent research has made great progress in realizing neural style transf...
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TIPRDC: Task-Independent Privacy-Respecting Data Crowdsourcing Framework with Anonymized Intermediate Representations
The success of deep learning partially benefits from the availability of...
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CSB-RNN: A Faster-than-Realtime RNN Acceleration Framework with Compressed Structured Blocks
Recurrent neural networks (RNNs) have been widely adopted in temporal se...
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The AVA-Kinetics Localized Human Actions Video Dataset
This paper describes the AVA-Kinetics localized human actions video data...
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Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification
Modern deep neural networks (DNNs) often require high memory consumption...
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Hybrid Models for Open Set Recognition
Open set recognition requires a classifier to detect samples not belongi...
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Near-Optimal Interference Exploitation 1-Bit Massive MIMO Precoding via Partial Branch-and-Bound
In this paper, we focus on 1-bit precoding for large-scale antenna syste...
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Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing
Deep Reinforcement Learning (RL) is proven powerful for decision making ...
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A Parallel Sparse Tensor Benchmark Suite on CPUs and GPUs
Tensor computations present significant performance challenges that impa...
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Hybrid Precoding Design for Reconfigurable Intelligent Surface aided mmWave Communication Systems
In this letter, we focus on the hybrid precoding (HP) design for the rec...
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Orthogonal Gradient Descent for Continual Learning
Neural networks are achieving state of the art and sometimes super-human...
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Computation Offloading for IoT in C-RAN: Optimization and Deep Learning
We consider computation offloading for Internet-of-things (IoT) applicat...
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Secure Interference Exploitation Precoding in MISO Wiretap Channel: Destructive Region Redefinition with Efficient Solutions
In this paper, we focus on the physical layer security for a K-user mult...
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DeepObfuscator: Adversarial Training Framework for Privacy-Preserving Image Classification
Deep learning has been widely utilized in many computer vision applicati...
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Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control
Many real-world sequential decision-making problems can be formulated as...
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UWB-GCN: Hardware Acceleration of Graph-Convolution-Network through Runtime Workload Rebalancing
The recent development of deep learning has mostly been focusing on Eucl...
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R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
Rotation detection is a challenging task due to the difficulties of loca...
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Boosted GAN with Semantically Interpretable Information for Image Inpainting
Image inpainting aims at restoring missing region of corrupted images, w...
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Interference Exploitation 1-Bit Massive MIMO Precoding: A Partial Branch-and-Bound Solution with Near-Optimal Performance
In this paper, we focus on 1-bit precoding approaches for downlink massi...
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Generative Image Inpainting with Submanifold Alignment
Image inpainting aims at restoring missing regions of corrupted images, ...
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Rethinking Classification and Localization for Cascade R-CNN
We extend the state-of-the-art Cascade R-CNN with a simple feature shari...
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Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions
Interference is traditionally viewed as a performance limiting factor in...
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Beam Allocation for Millimeter-Wave MIMO Tracking Systems
In this paper, we propose a new beam allocation strategy aiming to maxim...
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Cross-View Policy Learning for Street Navigation
The ability to navigate from visual observations in unfamiliar environme...
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Hybrid Precoder and Combiner for Imperfect Beam Alignment in mmWave MIMO Systems
In this letter, we aim to design a robust hybrid precoder and combiner a...
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Robust Hybrid Precoding for Beam Misalignment in Millimeter-Wave Communications
In this paper, we focus on the phenomenon of beam misalignment in Millim...
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Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect
High performance multi-GPU computing becomes an inevitable trend due to ...
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Improved Knowledge Distillation via Teacher Assistant: Bridging the Gap Between Student and Teacher
Despite the fact that deep neural networks are powerful models and achie...
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PASTA: A Parallel Sparse Tensor Algorithm Benchmark Suite
Tensor methods have gained increasingly attention from various applicati...
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