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07/07/2023
CODAG: Characterizing and Optimizing Decompression Algorithms for GPUs
Data compression and decompression have become vital components of big-d...
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05/22/2023
Distributionally Robust Optimization Efficiently Solves Offline Reinforcement Learning
Offline reinforcement learning aims to find the optimal policy from a pr...
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12/02/2022
Parallelizing Maximal Clique Enumeration on GPUs
We present a GPU solution for exact maximal clique enumeration (MCE) tha...
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11/25/2022
A Moral- and Event- Centric Inspection of Gender Bias in Fairy Tales at A Large Scale
Fairy tales are a common resource for young children to learn a language...
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11/08/2022
Submission-Aware Reviewer Profiling for Reviewer Recommender System
Assigning qualified, unbiased and interested reviewers to paper submissi...
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11/01/2022
Excel Spreadsheet Analyzer
Spreadsheets are widely used in various fields to do large numerical ana...
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10/17/2022
Extensible Proxy for Efficient NAS
Neural Architecture Search (NAS) has become a de facto approach in the r...
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10/11/2022
Can Language Models Be Specific? How?
A good speaker not only needs to be correct, but also has the ability to...
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10/09/2022
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT
We propose a novel application of prompting Pre-trained Language Models ...
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07/22/2022
HiKonv: Maximizing the Throughput of Quantized Convolution With Novel Bit-wise Management and Computation
Quantization for CNN has shown significant progress with the intention o...
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07/07/2022
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling
Graph convolutional networks (GCNs) have recently achieved great empiric...
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05/21/2022
DKG: A Descriptive Knowledge Graph for Explaining Relationships between Entities
In this paper, we propose Descriptive Knowledge Graph (DKG) - an open an...
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05/01/2022
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction
More and more investors and machine learning models rely on social media...
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04/01/2022
QuadraLib: A Performant Quadratic Neural Network Library for Architecture Optimization and Design Exploration
The significant success of Deep Neural Networks (DNNs) is highly promote...
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03/09/2022
GPU-Initiated On-Demand High-Throughput Storage Access in the BaM System Architecture
Graphics Processing Units (GPUs) have traditionally relied on the host C...
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01/21/2022
How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis
Self-training, a semi-supervised learning algorithm, leverages a large a...
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12/28/2021
HiKonv: High Throughput Quantized Convolution With Novel Bit-wise Management and Computation
Quantization for Convolutional Neural Network (CNN) has shown significan...
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11/10/2021
Graph Neural Network Training with Data Tiering
Graph Neural Networks (GNNs) have shown success in learning from graph-s...
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11/09/2021
MLHarness: A Scalable Benchmarking System for MLCommons
With the society's growing adoption of machine learning (ML) and deep le...
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10/12/2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks
The lottery ticket hypothesis (LTH) states that learning on a properly p...
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09/08/2021
Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs
With the constant increase of the number of quantum bits (qubits) in the...
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09/08/2021
Can Noise on Qubits Be Learned in Quantum Neural Network? A Case Study on QuantumFlow
In the noisy intermediate-scale quantum (NISQ) era, one of the key quest...
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08/20/2021
Open Relation Modeling: Learning to Define Relations between Entities
Relations between entities can be represented by different instances, e....
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08/04/2021
Generic Neural Architecture Search via Regression
Most existing neural architecture search (NAS) algorithms are dedicated ...
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06/16/2021
Global Rhythm Style Transfer Without Text Transcriptions
Prosody plays an important role in characterizing the style of a speaker...
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05/27/2021
Measuring Fine-Grained Domain Relevance of Terms: A Hierarchical Core-Fringe Approach
We propose to measure fine-grained domain relevance - the degree that a ...
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05/19/2021
Heterogeneous Contrastive Learning
With the advent of big data across multiple high-impact applications, we...
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04/27/2021
K-Clique Counting on GPUs
Counting k-cliques in a graph is an important problem in graph analysis ...
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03/25/2021
Enabling Design Methodologies and Future Trends for Edge AI: Specialization and Co-design
Artificial intelligence (AI) technologies have dramatically advanced in ...
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03/04/2021
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture
Graph Convolutional Networks (GCNs) are increasingly adopted in large-sc...
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01/20/2021
PyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses
With the increasing adoption of graph neural networks (GNNs) in the mach...
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01/19/2021
Safer Illinois and RokWall: Privacy Preserving University Health Apps for COVID-19
COVID-19 has fundamentally disrupted the way we live. Government bodies,...
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12/28/2020
TEMPI: An Interposed MPI Library with a Canonical Representation of CUDA-aware Datatypes
MPI derived datatypes are an abstraction that simplifies handling of non...
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12/18/2020
When Machine Learning Meets Quantum Computers: A Case Study
Along with the development of AI democratization, the machine learning a...
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11/23/2020
Interpretable Visual Reasoning via Induced Symbolic Space
We study the problem of concept induction in visual reasoning, i.e., ide...
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11/21/2020
Efficient Neural Network Implementation with Quadratic Neuron
Previous works proved that the combination of the linear neuron network ...
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10/14/2020
Effective Algorithm-Accelerator Co-design for AI Solutions on Edge Devices
High quality AI solutions require joint optimization of AI algorithms, s...
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10/05/2020
Exploring Semantic Capacity of Terms
We introduce and study semantic capacity of terms. For example, the sema...
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08/28/2020
DNNExplorer: A Framework for Modeling and Exploring a Novel Paradigm of FPGA-based DNN Accelerator
Existing FPGA-based DNN accelerators typically fall into two design para...
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08/24/2020
Tearing Down the Memory Wall
We present a vision for the Erudite architecture that redefines the comp...
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07/31/2020
Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases
When the training data are maliciously tampered, the predictions of the ...
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07/28/2020
At-Scale Sparse Deep Neural Network Inference with Efficient GPU Implementation
This paper presents GPU performance optimization and scaling results for...
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07/18/2020
ICA-UNet: ICA Inspired Statistical UNet for Real-time 3D Cardiac Cine MRI Segmentation
Real-time cine magnetic resonance imaging (MRI) plays an increasingly im...
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06/26/2020
Can Quantum Computers Learn Like Classical Computers? A Co-Design Framework for Machine Learning and Quantum Circuits
Despite the pursuit of quantum supremacy in various applications, the po...
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06/25/2020
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
Although graph neural networks (GNNs) have made great progress recently ...
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06/12/2020
EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal In GPUs
Modern analytics and recommendation systems are increasingly based on gr...
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05/06/2020
A Multi-Perspective Architecture for Semantic Code Search
The ability to match pieces of code to their corresponding natural langu...
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05/06/2020
EDD: Efficient Differentiable DNN Architecture and Implementation Co-search for Embedded AI Solutions
High quality AI solutions require joint optimization of AI algorithms an...
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04/02/2020
Alleviating Semantic-level Shift: A Semi-supervised Domain Adaptation Method for Semantic Segmentation
Learning segmentation from synthetic data and adapting to real data can ...
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03/18/2020