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08/03/2023
LiDAR-Camera Panoptic Segmentation via Geometry-Consistent and Semantic-Aware Alignment
3D panoptic segmentation is a challenging perception task that requires ...
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06/12/2023
Underwater Acoustic Target Recognition based on Smoothness-inducing Regularization and Spectrogram-based Data Augmentation
Underwater acoustic target recognition is a challenging task owing to th...
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05/31/2023
Underwater-Art: Expanding Information Perspectives With Text Templates For Underwater Acoustic Target Recognition
Underwater acoustic target recognition is an intractable task due to the...
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05/31/2023
Learning Music Sequence Representation from Text Supervision
Music representation learning is notoriously difficult for its complex h...
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05/31/2023
Adaptive ship-radiated noise recognition with learnable fine-grained wavelet transform
Analyzing the ocean acoustic environment is a tricky task. Background no...
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04/24/2023
Advancing underwater acoustic target recognition via adaptive data pruning and smoothness-inducing regularization
Underwater acoustic recognition for ship-radiated signals has high pract...
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04/18/2023
NPS: A Framework for Accurate Program Sampling Using Graph Neural Network
With the end of Moore's Law, there is a growing demand for rapid archite...
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04/11/2023
High-performance and Scalable Software-based NVMe Virtualization Mechanism with I/O Queues Passthrough
NVMe(Non-Volatile Memory Express) is an industry standard for solid-stat...
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03/14/2023
Gamora: Graph Learning based Symbolic Reasoning for Large-Scale Boolean Networks
Reasoning high-level abstractions from bit-blasted Boolean networks (BNs...
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02/07/2023
High-Resolution GAN Inversion for Degraded Images in Large Diverse Datasets
The last decades are marked by massive and diverse image data, which sho...
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12/09/2022
Weakly Supervised Semantic Segmentation for Large-Scale Point Cloud
Existing methods for large-scale point cloud semantic segmentation requi...
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11/16/2022
AdaTriplet-RA: Domain Matching via Adaptive Triplet and Reinforced Attention for Unsupervised Domain Adaptation
Unsupervised domain adaption (UDA) is a transfer learning task where the...
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11/10/2022
A Comprehensive Survey on Distributed Training of Graph Neural Networks
Graph neural networks (GNNs) have been demonstrated to be a powerful alg...
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11/02/2022
Rethinking the Metric in Few-shot Learning: From an Adaptive Multi-Distance Perspective
Few-shot learning problem focuses on recognizing unseen classes given a ...
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10/29/2022
Enabling Data Movement and Computation Pipelining in Deep Learning Compiler
Pipelining between data loading and computation is a critical tensor pro...
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09/23/2022
Faith: An Efficient Framework for Transformer Verification on GPUs
Transformer verification draws increasing attention in machine learning ...
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09/16/2022
Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learning
Weakly supervised point cloud semantic segmentation methods that require...
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09/05/2022
Prototype-Aware Heterogeneous Task for Point Cloud Completion
Point cloud completion, which aims at recovering original shape informat...
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08/31/2022
Attentive pooling for Group Activity Recognition
In group activity recognition, hierarchical framework is widely adopted ...
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08/30/2022
Boosting Night-time Scene Parsing with Learnable Frequency
Night-Time Scene Parsing (NTSP) is essential to many vision applications...
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08/11/2022
MILAN: Masked Image Pretraining on Language Assisted Representation
Self-attention based transformer models have been dominating many comput...
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08/09/2022
Characterizing and Understanding HGNNs on GPUs
Heterogeneous graph neural networks (HGNNs) deliver powerful capacity in...
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07/28/2022
Predicting the Output Structure of Sparse Matrix Multiplication with Sampled Compression Ratio
Sparse general matrix multiplication (SpGEMM) is a fundamental building ...
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07/19/2022
MoEC: Mixture of Expert Clusters
Sparsely Mixture of Experts (MoE) has received great interest due to its...
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07/15/2022
Multi-node Acceleration for Large-scale GCNs
Limited by the memory capacity and compute power, singe-node graph convo...
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06/20/2022
Variational Distillation for Multi-View Learning
Information Bottleneck (IB) based multi-view learning provides an inform...
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06/15/2022
Cost-Aware Exploration for Chiplet-Based Architecture with Advanced Packaging Technologies
The chiplet-based System-in-Package (SiP) technology enables more design...
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06/15/2022
OpSparse: a Highly Optimized Framework for Sparse General Matrix Multiplication on GPUs
Sparse general matrix multiplication (SpGEMM) is an important and expens...
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06/14/2022
Accelerating CPU-Based Sparse General Matrix Multiplication With Binary Row Merging
Sparse general matrix multiplication (SpGEMM) is a fundamental building ...
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06/04/2022
The Spike Gating Flow: A Hierarchical Structure Based Spiking Neural Network for Online Gesture Recognition
Action recognition is an exciting research avenue for artificial intelli...
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06/01/2022
Task-Specific Expert Pruning for Sparse Mixture-of-Experts
The sparse Mixture-of-Experts (MoE) model is powerful for large-scale pr...
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04/12/2022
Toward Robust Spiking Neural Network Against Adversarial Perturbation
As spiking neural networks (SNNs) are deployed increasingly in real-worl...
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03/31/2022
LAKe-Net: Topology-Aware Point Cloud Completion by Localizing Aligned Keypoints
Point cloud completion aims at completing geometric and topological shap...
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03/09/2022
Shfl-BW: Accelerating Deep Neural Network Inference with Tensor-Core Aware Weight Pruning
Weight pruning in deep neural networks (DNNs) can reduce storage and com...
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02/28/2022
Dynamic N:M Fine-grained Structured Sparse Attention Mechanism
Transformers are becoming the mainstream solutions for various tasks lik...
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02/23/2022
Alleviating Datapath Conflicts and Design Centralization in Graph Analytics Acceleration
Previous graph analytics accelerators have achieved great improvement on...
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02/10/2022
Survey on Graph Neural Network Acceleration: An Algorithmic Perspective
Graph neural networks (GNNs) have been a hot spot of recent research and...
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01/20/2022
Hybrid Graph Models for Logic Optimization via Spatio-Temporal Information
Despite the stride made by machine learning (ML) based performance model...
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01/18/2022
High-Level Synthesis Performance Prediction using GNNs: Benchmarking, Modeling, and Advancing
Agile hardware development requires fast and accurate circuit quality ev...
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12/21/2021
Structured Semantic Transfer for Multi-Label Recognition with Partial Labels
Multi-label image recognition is a fundamental yet practical task becaus...
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12/21/2021
Compact Multi-level Sparse Neural Networks with Input Independent Dynamic Rerouting
Deep neural networks (DNNs) have shown to provide superb performance in ...
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12/20/2021
Load-balanced Gather-scatter Patterns for Sparse Deep Neural Networks
Deep neural networks (DNNs) have been proven to be effective in solving ...
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11/26/2021
Towards Efficient Ansatz Architecture for Variational Quantum Algorithms
Variational quantum algorithms are expected to demonstrate the advantage...
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11/26/2021
Mapping Surface Code to Superconducting Quantum Processors
In this paper, we formally describe the three challenges of mapping surf...
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11/26/2021
QECV: Quantum Error Correction Verification
Quantum Error Correction (QEC) is essential for fault-tolerant quantum c...
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11/25/2021
Mitigating Noise-Induced Gradient Vanishing in Variational Quantum Algorithm Training
Variational quantum algorithms are expected to demonstrate the advantage...
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11/25/2021
Exploring Versatile Prior for Human Motion via Motion Frequency Guidance
Prior plays an important role in providing the plausible constraint on h...
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10/21/2021
Transformer Acceleration with Dynamic Sparse Attention
Transformers are the mainstream of NLP applications and are becoming inc...
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09/13/2021
Program-to-Circuit: Exploiting GNNs for Program Representation and Circuit Translation
Circuit design is complicated and requires extensive domain-specific exp...
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07/25/2021
