Výsledky vyhledávání - "Computing methodologies Machine learning Machine learning approaches"

PrefixRL: Optimization of Parallel Prefix Circuits using Deep Reinforcement Learning Autor Roy, Rajarshi, Raiman, Jonathan, Kant, Neel, Elkin, Ilyas, Kirby, Robert, Siu, Michael, Oberman, Stuart, Godil, Saad, Catanzaro, Bryan

“…In this work, we present a reinforcement learning (RL) based approach to designing parallel prefix circuits such as adders or priority encoders that are…”
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Dual-side Sparse Tensor Core Autor Wang, Yang, Zhang, Chen, Xie, Zhiqiang, Guo, Cong, Liu, Yunxin, Leng, Jingwen

“…Leveraging sparsity in deep neural network (DNN) models is promising for accelerating model inference. Yet existing GPUs can only leverage the sparsity from…”
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FactorHD: A Hyperdimensional Computing Model for Multi-Object Multi-Class Representation and Factorization Autor Zhou, Yifei, Huang, Xuchu, Ni, Chenyu, Zhou, Min, Yan, Zheyu, Yin, Xunzhao, Zhuo, Cheng

“…Neuro-symbolic artificial intelligence (neurosymbolic AI) excels in logical analysis and reasoning. Hyperdimensional Computing (HDC), a promising braininspired…”
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QEDCartographer: Automating Formal Verification Using Reward-Free Reinforcement Learning Autor Sanchez-Stern, Alex, Varghese, Abhishek, Kaufman, Zhanna, Zhang, Dylan, Ringer, Talia, Brun, Yuriy

“…Formal verification is a promising method for producing reliable software, but the difficulty of manually writing verification proofs severely limits its…”
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Semantically Enhanced Software Traceability Using Deep Learning Techniques Autor Jin Guo, Jinghui Cheng, Cleland-Huang, Jane

“…In most safety-critical domains the need for traceability is prescribed by certifying bodies. Trace links are generally created among requirements, design,…”
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GENESYS: A novel evolutionary program synthesis tool with continuous optimization Autor Mandal, Shantanu, Anderson, Todd A, Turek, Javier, Gottschlich, Justin, Muzahid, Abdullah

“…Automatic software generation based on some specification is known as program synthesis. Most existing approaches formulate program synthesis as a search…”
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Diversity Drives Fairness: Ensemble of Higher Order Mutants for Intersectional Fairness of Machine Learning Software Autor Chen, Zhenpeng, Li, Xinyue, Zhang, Jie M., Sarro, Federica, Liu, Yang

“…Intersectional fairness is a critical requirement for Machine Learning (ML) software, demanding fairness across subgroups defined by multiple protected…”
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Softermax: Hardware/Software Co-Design of an Efficient Softmax for Transformers Autor Stevens, Jacob R., Venkatesan, Rangharajan, Dai, Steve, Khailany, Brucek, Raghunathan, Anand

“…Transformers have transformed the field of natural language processing. Their superior performance is largely attributed to the use of stacked "self-attention"…”
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The Devil is in the Tails: How Long-Tailed Code Distributions Impact Large Language Models Autor Zhout, Xin, Kim, Kisub, Xu, Bowen, Liu, Jiakun, Han, DongGyun, Lo, David

“…Learning-based techniques, especially advanced Large Language Models (LLMs) for code, have gained considerable popularity in various software engineering (SE)…”
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An Extension to Basis-Hypervectors for Learning from Circular Data in Hyperdimensional Computing Autor Nunes, Igor, Heddes, Mike, Givargis, Tony, Nicolau, Alexandru

“…Hyperdimensional Computing (HDC) is a computation framework based on random vector spaces, particularly useful for machine learning in resource-constrained…”
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Code Difference Guided Adversarial Example Generation for Deep Code Models Autor Tian, Zhao, Chen, Junjie, Jin, Zhi

“…Adversarial examples are important to test and enhance the robustness of deep code models. As source code is discrete and has to strictly stick to complex…”
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Rescuing memristor-based neuromorphic design with high defects Autor Chenchen Liu, Miao Hu, Strachan, John Paul, Hai Li

“…Memristor-based synaptic network has been widely investigated and applied to neuromorphic computing systems for the fast computation and low design cost. As…”
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PertNAS: Architectural Perturbations for Memory-Efficient Neural Architecture Search Autor Ahmad, Afzal, Xie, Zhiyao, Zhang, Wei

“…Differentiable Neural Architecture Search (NAS) relies on aggressive weight-sharing to reduce its search cost. This leads to GPU-memory bottlenecks that hamper…”
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The Logic of Graph Neural Networks Autor Grohe, Martin

“…Graph neural networks (GNNs) are deep learning architectures for machine learning problems on graphs. It has recently been shown that the expressiveness of…”
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EditSum: A Retrieve-and-Edit Framework for Source Code Summarization Autor Li, Jia Allen, Li, Yongmin, Li, Ge, Hu, Xing, Xia, Xin, Jin, Zhi

“…Existing studies show that code summaries help developers understand and maintain source code. Unfortunately, these summaries are often missing or outdated in…”
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Making Fair ML Software using Trustworthy Explanation Autor Chakraborty, Joymallya, Peng, Kewen, Menzies, Tim

“…Machine learning software is being used in many applications (finance, hiring, admissions, criminal justice) having huge social impact. But sometimes the…”
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Google Neural Network Models for Edge Devices: Analyzing and Mitigating Machine Learning Inference Bottlenecks Autor Boroumand, Amirali, Ghose, Saugata, Akin, Berkin, Narayanaswami, Ravi, Oliveira, Geraldo F., Ma, Xiaoyu, Shiu, Eric, Mutlu, Onur

“…Emerging edge computing platforms often contain machine learning (ML) accelerators that can accelerate inference for a wide range of neural network (NN)…”
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UniGenCoder: Merging SEQ2SEQ and SEQ2TREE Paradigms for Unified Code Generation Autor Shao, Liangying, Yan, Yanfu, Poshyvanyk, Denys, Su, Jinsong

“…Deep learning-based code generation has completely transformed the way developers write programs today. Existing approaches to code generation have focused…”
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MAGIKA: AI-Powered Content-Type Detection Autor Fratantonio, Yanick, Invernizzi, Luca, Farah, Loua, Thomas, Kurt, Zhang, Marina, Albertini, Ange, Galilee, Francois, Metitieri, Giancarlo, Cretin, Julien, Petit-Bianco, Alex, Tao, David, Bursztein, Elie

“…The task of content-type detection-which entails identifying the data encoded in an arbitrary byte sequence-is critical for operating systems, development,…”
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Fast and Efficient Information Transmission with Burst Spikes in Deep Spiking Neural Networks Autor Park, Seongsik, Kim, Seijoon, Choe, Hyeokjun, Yoon, Sungroh

“…Spiking neural networks (SNNs) are considered as one of the most promising artificial neural networks due to their energy-efficient computing capability…”
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