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A Survey of Machine Learning for Computer Architecture and Systems
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Redox‐Based Resistive Switching Memories – Nanoionic Mechanisms, Prospects, and Challenges
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The Weighted Majority Algorithm
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Nonlinear Regression with R
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Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms
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Unsupervised Anomaly-Based Malware Detection Using Hardware Features
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Principal component analysis
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Adaptive job routing and scheduling
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Empirical prediction models for adaptive resource provisioning in the cloud
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Hard drive failure prediction using Decision Trees
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Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks
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Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
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Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts
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Human-level control through deep reinforcement learning
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Mastering the game of Go without human knowledge
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Grandmaster level in StarCraft II using multi-agent reinforcement learning
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An Introduction to Kernel and Nearest-Neighbor Nonparametric Regression
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Simics: A full system simulation platform
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High-Definition Routing Congestion Prediction for Large-Scale FPGAs
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HL-Pow: A Learning-Based Power Modeling Framework for High-Level Synthesis
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DRiLLS: Deep Reinforcement Learning for Logic Synthesis
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MLNoC: A Machine Learning Based Approach to NoC Design
inferredcites →https://doi.org/10.1109/cgo.2006.37openalex-snapshot
Using Machine Learning to Focus Iterative Optimization
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Synthesizing benchmarks for predictive modeling
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Efficient Autoscaling in the Cloud Using Predictive Models for Workload Forecasting
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PRESS: PRedictive Elastic ReSource Scaling for cloud systems
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Going deeper with convolutions
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Fully convolutional networks for semantic segmentation
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Deep Residual Learning for Image Recognition
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Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
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A Machine Learning Framework to Identify Detailed Routing Short Violations from a Placed Netlist
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Dynamic Management of Key States for Reinforcement Learning-assisted Garbage Collection to Reduce Long Tail Latency in SSD
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MLParest: Machine Learning based Parasitic Estimation for Custom Circuit Design
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ParaGraph: Layout Parasitics and Device Parameter Prediction using Graph Neural Networks
inferredcites →https://doi.org/10.1109/dac18072.2020.9218621openalex-snapshot
Closing the Design Loop: Bayesian Optimization Assisted Hierarchical Analog Layout Synthesis
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GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning
inferredcites →https://doi.org/10.1109/dsn.2014.44openalex-snapshot
Hard Drive Failure Prediction Using Classification and Regression Trees
inferredcites →https://doi.org/10.1109/epeps.2016.7835438openalex-snapshot
Machine learning in physical design
inferredcites →https://doi.org/10.1109/fccm.2016.28openalex-snapshot
Improving Classification Accuracy of a Machine Learning Approach for FPGA Timing Closure
inferredcites →https://doi.org/10.1109/fccm.2018.00029openalex-snapshot
Fast and Accurate Estimation of Quality of Results in High-Level Synthesis with Machine Learning
inferredcites →https://doi.org/10.1109/fpl.2018.00079openalex-snapshot
Machine-Learning Based Congestion Estimation for Modern FPGAs
inferredcites →https://doi.org/10.1109/fpl.2019.00069openalex-snapshot
Pyramid: Machine Learning Framework to Estimate the Optimal Timing and Resource Usage of a High-Level Synthesis Design
inferredcites →https://doi.org/10.1109/fuzz.2002.1004983openalex-snapshot
Adaptive coordination among fuzzy reinforcement learning agents performing distributed dynamic load balancing
inferredcites →https://doi.org/10.1109/hpca.2001.903263openalex-snapshot
Dynamic branch prediction with perceptrons
inferredcites →https://doi.org/10.1109/hpca.2006.1598116openalex-snapshot
Construction and Use of Linear Regression Models for Processor Performance Analysis
inferredcites →https://doi.org/10.1109/hpca.2007.346211openalex-snapshot
Illustrative Design Space Studies with Microarchitectural Regression Models
inferredcites →https://doi.org/10.1109/hpca.2012.6168945openalex-snapshot
MORSE: Multi-objective reconfigurable self-optimizing memory scheduler
inferredcites →https://doi.org/10.1109/hpca.2014.6835941openalex-snapshot
Up by their bootstraps: Online learning in Artificial Neural Networks for CMP uncore power management
inferredcites →https://doi.org/10.1109/hpca.2015.7056063openalex-snapshot
GPGPU performance and power estimation using machine learning
inferredcites →https://doi.org/10.1109/hpca.2017.43openalex-snapshot
Maximizing Cache Performance Under Uncertainty
inferredcites →https://doi.org/10.1109/hpca.2018.00048openalex-snapshot
Extending the Power-Efficiency and Performance of Photonic Interconnects for Heterogeneous Multicores with Machine Learning
inferredcites →https://doi.org/10.1109/hpca47549.2020.00058openalex-snapshot
Experiences with ML-Driven Design: A NoC Case Study
inferredcites →https://doi.org/10.1109/hpcs.2018.00030openalex-snapshot
Machine Learning Approach for Loop Unrolling Factor Prediction in High Level Synthesis
inferredcites →https://doi.org/10.1109/hpcsim.2016.7568398openalex-snapshot
MultiObjective GPU design space exploration optimization
inferredcites →https://doi.org/10.1109/icac.2005.4openalex-snapshot
A Reinforcement Learning Framework for Dynamic Resource Allocation: First Results.
inferredcites →https://doi.org/10.1109/icac.2017.29openalex-snapshot
ESP: A Machine Learning Approach to Predicting Application Interference
inferredcites →https://doi.org/10.1109/icassp40776.2020.9054042openalex-snapshot
Electric Analog Circuit Design with Hypernetworks And A Differential Simulator
inferredcites →https://doi.org/10.1109/iccad45719.2019.8942062openalex-snapshot
BagNet: Berkeley Analog Generator with Layout Optimizer Boosted with Deep Neural Networks
inferredcites →https://doi.org/10.1109/iccad45719.2019.8942063openalex-snapshot
GAN-CTS: A Generative Adversarial Framework for Clock Tree Prediction and Optimization
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GeniusRoute: A New Analog Routing Paradigm Using Generative Neural Network Guidance
inferredcites →https://doi.org/10.1109/iccd.2011.6081385openalex-snapshot
An optimized scaled neural branch predictor
inferredcites →https://doi.org/10.1109/iccd.2014.6974668openalex-snapshot
Accurate prediction of detailed routing congestion using supervised data learning
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BEOL stack-aware routability prediction from placement using data mining techniques
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Characterizing On-Chip Traffic Patterns in General-Purpose GPUs: A Deep Learning Approach
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Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning
inferredcites →https://doi.org/10.1109/icpp.2008.36openalex-snapshot
Machine Learning Models to Predict Performance of Computer System Design Alternatives
inferredcites →https://doi.org/10.1109/icpp.2012.31openalex-snapshot
GreenGPU: A Holistic Approach to Energy Efficiency in GPU-CPU Heterogeneous Architectures
inferredcites →https://doi.org/10.1109/icpp.2014.46openalex-snapshot
Adaptive Configuration Selection for Power-Constrained Heterogeneous Systems
inferredcites →https://doi.org/10.1109/icppw.2016.43openalex-snapshot
Block2Vec: A Deep Learning Strategy on Mining Block Correlations in Storage Systems
inferredcites →https://doi.org/10.1109/icra.2017.7989385openalex-snapshot
Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates
inferredcites →https://doi.org/10.1109/iedm.2005.1609379openalex-snapshot
A novel nonvolatile memory with spin torque transfer magnetization switching: spin-ram
inferredcites →https://doi.org/10.1109/iitsi.2010.74openalex-snapshot
Research on k-means Clustering Algorithm: An Improved k-means Clustering Algorithm
inferredcites →https://doi.org/10.1109/ijcnn.2001.938732openalex-snapshot
A neuro-evolution method for dynamic resource allocation on a chip multiprocessor
inferredcites →https://doi.org/10.1109/ipdps.2005.323openalex-snapshot
Packet Routing in Dynamically Changing Networks on Chip
inferredcites →https://doi.org/10.1109/iscas.2018.8351580openalex-snapshot
Neuro-NoC: Energy Optimization in Heterogeneous Many-Core NoC using Neural Networks in Dark Silicon Era
inferredcites →https://doi.org/10.1109/iscas.2018.8351885openalex-snapshot
Deep Learning for Logic Optimization Algorithms
inferredcites →https://doi.org/10.1109/ispass.2011.5762738openalex-snapshot
Mechanistic-empirical processor performance modeling for constructing CPI stacks on real hardware
inferredcites →https://doi.org/10.1109/ispass.2012.6189201openalex-snapshot
Stargazer: Automated regression-based GPU design space exploration
inferredcites →https://doi.org/10.1109/isqed.2019.8697679openalex-snapshot
Approximate Logic Synthesis: A Reinforcement Learning-Based Technology Mapping Approach
inferredcites →https://doi.org/10.1109/isscc.2017.7870350openalex-snapshot
14.2 DNPU: An 8.1TOPS/W reconfigurable CNN-RNN processor for general-purpose deep neural networks
inferredcites →https://doi.org/10.1109/isscc19947.2020.9063049openalex-snapshot
1.1 The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design
inferredcites →https://doi.org/10.1109/isvlsi49217.2020.00015openalex-snapshot
Exploring a Machine Learning Approach to Performance Driven Analog IC Placement
inferredcites →https://doi.org/10.1109/jetcas.2016.2547718openalex-snapshot
Recent Progress in Phase-ChangeMemory Technology
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Efficient Processing of Deep Neural Networks: A Tutorial and Survey
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Design Space Exploration of Memory Controller Placement in Throughput Processors with Deep Learning
inferredcites →https://doi.org/10.1109/mascots.2013.9openalex-snapshot
Towards Machine Learning-Based Auto-tuning of MapReduce
inferredcites →https://doi.org/10.1109/mic.2007.21openalex-snapshot
Reinforcement Learning in Autonomic Computing: A Manifesto and Case Studies
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A Predictive Performance Model for Superscalar Processors
inferredcites →https://doi.org/10.1109/micro.2008.4771797openalex-snapshot
CPR: Composable performance regression for scalable multiprocessor models
inferredcites →https://doi.org/10.1109/micro.2008.4771801openalex-snapshot
Coordinated management of multiple interacting resources in chip multiprocessors: A machine learning approach
inferredcites →https://doi.org/10.1109/micro.2008.4771812openalex-snapshot
Low-power, high-performance analog neural branch prediction
inferredcites →https://doi.org/10.1109/micro.2010.14openalex-snapshot
A Predictive Model for Dynamic Microarchitectural Adaptivity Control
inferredcites →https://doi.org/10.1109/micro.2012.45openalex-snapshot
Inferred Models for Dynamic and Sparse Hardware-Software Spaces
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Neural Acceleration for General-Purpose Approximate Programs
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DaDianNao: A Machine-Learning Supercomputer
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DiffTune: Optimizing CPU Simulator Parameters with Learned Differentiable Surrogates
inferredcites →https://doi.org/10.1109/micro50266.2020.00058openalex-snapshot
ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement Learning
inferredcites →https://doi.org/10.1109/mm.2007.61openalex-snapshot
Spatial Sampling and Regression Strategies
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Dynamic Multicore Resource Management: A Machine Learning Approach
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Adaptive Power Capping for Servers with Multithreaded Workloads
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Near-Data Processing: Insights from a MICRO-46 Workshop
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Accelerating Chip Design With Machine Learning
inferredcites →https://doi.org/10.1109/msst.2013.6558427openalex-snapshot
Proactive drive failure prediction for large scale storage systems
inferredcites →https://doi.org/10.1109/nocs.2012.10openalex-snapshot
HARAQ: Congestion-Aware Learning Model for Highly Adaptive Routing Algorithm in On-Chip Networks
inferredcites →https://doi.org/10.1109/noms.2012.6212065openalex-snapshot
Workload characterization and prediction in the cloud: A multiple time series approach
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End-to-End Deep Learning of Optimization Heuristics
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Learning-based analytical cross-platform performance prediction
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Predicting GPU Performance from CPU Runs Using Machine Learning
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A Machine Learning Approach for Performance Prediction and Scheduling on Heterogeneous CPUs
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Accelerating chip design with machine learning: From pre-silicon to post-silicon
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A Holistic Approach Towards Intelligent Hotspot Prevention in Network-on-Chip-Based Multicores
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A Q-Learning Based Self-Adaptive I/O Communication for 2.5D Integrated Many-Core Microprocessor and Memory
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Health Status Assessment and Failure Prediction for Hard Drives with Recurrent Neural Networks
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Dynamic Voltage and Frequency Scaling in NoCs with Supervised and Reinforcement Learning Techniques
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Learning-Based Application-Agnostic 3D NoC Design for Heterogeneous Manycore Systems
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Intelligent Hotspot Prediction for Network-on-Chip-Based Multicore Systems
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Profit: Priority and Power/Performance Optimization for Many-Core Systems
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RePlAce: Advancing Solution Quality and Routability Validation in Global Placement
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Workload Prediction Using ARIMA Model and Its Impact on Cloud Applications’ QoS
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Reinforcement Learning: An Introduction
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A Comprehensive Survey on Graph Neural Networks
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Learning agile and dynamic motor skills for legged robots
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Interleaved Caching with Access Graphs
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Piecewise Linear Branch Prediction
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Accurate and efficient regression modeling for microarchitectural performance and power prediction
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Efficiently exploring architectural design spaces via predictive modeling
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Accurate and efficient regression modeling for microarchitectural performance and power prediction
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Online power-performance adaptation of multithreaded programs using hardware event-based prediction
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Methods of inference and learning for performance modeling of parallel applications
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Integrated CPU and l2 cache voltage scaling using machine learning
inferredcites →https://doi.org/10.1145/1273444.1254773openalex-snapshot
Integrated CPU and l2 cache voltage scaling using machine learning
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Self-Optimizing Memory Controllers
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Feature selection and policy optimization for distributed instruction placement using reinforcement learning
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Prediction models for multi-dimensional power-performance optimization on many cores
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Machine learning-based prefetch optimization for data center applications
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A reconfigurable fault-tolerant deflection routing algorithm based on reinforcement learning for network-on-chip
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Power-aware performance increase via core/uncore reinforcement control for chip-multiprocessors
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Mitigating the compiler optimization phase-ordering problem using machine learning
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Mitigating the compiler optimization phase-ordering problem using machine learning
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Evidence-based static branch prediction using machine learning
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On learning-based methods for design-space exploration with high-level synthesis
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On the feasibility of online malware detection with performance counters
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A circuit-architecture co-optimization framework for exploring nonvolatile memory hierarchies
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Code completion with statistical language models
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Scalable Power Management Using Multilevel Reinforcement Learning for Multiprocessors
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Code completion with statistical language models
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A Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints
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Reinforcement Learning for Thermal-aware Many-core Task Allocation
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Semantic locality and context-based prefetching using reinforcement learning
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A Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints
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Prediction-guided performance-energy trade-off for interactive applications
inferredcites →https://doi.org/10.1145/2830772.2830780openalex-snapshot
Cross-architecture performance prediction (XAPP) using CPU code to predict GPU performance
inferredcites →https://doi.org/10.1145/2830772.2830810openalex-snapshot
Neural acceleration for GPU throughput processors
inferredcites →https://doi.org/10.1145/2872887.2749473openalex-snapshot
Semantic locality and context-based prefetching using reinforcement learning
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Accurate phase-level cross-platform power and performance estimation
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Flip-flop clustering by weighted K-means algorithm
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Quest for high-performance bufferless NoCs with single-cycle express paths and self-learning throttling
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Energy-efficient and reliable 3D network-on-chip (NoC): architectures and optimization algorithms
inferredcites →https://doi.org/10.1145/2967938.2967940openalex-snapshot
Scheduling Techniques for GPU Architectures with Processing-In-Memory Capabilities
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Automatic generation of efficient accelerators for reconfigurable hardware
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Automatic Database Management System Tuning Through Large-scale Machine Learning
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Voltage Regulator Efficiency Aware Power Management
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Efficient Hierarchical Performance Modeling for Integrated Circuits via Bayesian Co-Learning
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Voltage Regulator Efficiency Aware Power Management
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Neural Adaptive Video Streaming with Pensieve
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Multiperspective reuse prediction
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inferredcites →https://doi.org/10.1145/3132402.3132405openalex-snapshot
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inferredcites →https://doi.org/10.1145/3183713.3196909openalex-snapshot
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inferredcites →https://doi.org/10.1145/3195970.3196026openalex-snapshot
Developing synthesis flows without human knowledge
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DATE: Dual Prompt Learning with Information Bottleneck for Graph Out-of-Distribution Generalization
inferred← citeshttps://doi.org/10.1145/3746252.3760961openalex-snapshot
GraFS: An Integrated GNN-LLM Approach for Inferring Best Functional Substitute Products
inferred← citeshttps://doi.org/10.1145/3746252.3761088openalex-snapshot
Stamp: Semantic-Aware Sub-trajectory Anomaly Detection with Diffusion Multi-model Pool for Evolving Data Streams
inferred← citeshttps://doi.org/10.1145/3746252.3761187openalex-snapshot
Hybrid 2 : Distributed GNN Training System Enhanced by Dual-Hybrid for Sampling and Loading
inferred← citeshttps://doi.org/10.1145/3746252.3761228openalex-snapshot
Rethinking Client-oriented Federated Graph Learning
inferred← citeshttps://doi.org/10.1145/3746252.3761244openalex-snapshot
A Node-Aware Dynamic Quantization Approach for Graph Collaborative Filtering
inferred← citeshttps://doi.org/10.1145/3746252.3761256openalex-snapshot
PathLens: Structurally Enhancing Heterophilic Graphs for GNNs
inferred← citeshttps://doi.org/10.1145/3746252.3761357openalex-snapshot
TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations
inferred← citeshttps://doi.org/10.1145/3746252.3761542openalex-snapshot
Billion-Scale Graph Deep Learning Framework for Ads Recommendation
inferred← citeshttps://doi.org/10.1145/3757736openalex-snapshot
Position-aware Graph Transformer for Recommendation
inferred← citeshttps://doi.org/10.1145/3760763openalex-snapshot
Revisiting LightGCN: Unexpected Inflexibility, Inconsistency, and A Remedy Towards Improved Recommendation
inferred← citeshttps://doi.org/10.1145/3761807openalex-snapshot
Lemonade: Learning-based Heterogeneous Metadata Offloading for Disaggregated Memory
inferred← citeshttps://doi.org/10.1145/3762665openalex-snapshot
MMHCL: Multi-Modal Hypergraph Contrastive Learning for Recommendation
inferred← citeshttps://doi.org/10.1145/3766882.3767178openalex-snapshot
Easing the path to deployment in ML4Sys through FPGAs
inferred← citeshttps://doi.org/10.1145/3767326openalex-snapshot
Explainable Surgical Procedures Recommender System Leveraging Large Language Models
inferred← citeshttps://doi.org/10.1145/3767695.3769497openalex-snapshot
Data Usage Privacy Auditing for Semi-supervised GNNs
inferred← citeshttps://doi.org/10.1145/3773966.3777924openalex-snapshot
SoftHist: Teaching Graph Injection Attackers to Camouflage with Memory
inferred← citeshttps://doi.org/10.1145/3773966.3779398openalex-snapshot
Transfer Learning via User-Item Graph Convolution for Enhanced Cross-Domain Recommendation
inferred← citeshttps://doi.org/10.1145/3774904.3792079openalex-snapshot
Multi-Source Unsupervised Graph Domain Adaptation via Concise Propagation–Transformation Pipeline
inferred← citeshttps://doi.org/10.1145/3774904.3792102openalex-snapshot
The Devil Within, The Cure Without: Securing Locally Private Graph Learning under Poisoning
inferred← citeshttps://doi.org/10.1145/3774904.3792192openalex-snapshot
Multi-view Semantic Contrastive Alignment for Multimodal Recommendation
inferred← citeshttps://doi.org/10.1145/3774904.3792546openalex-snapshot
LLM-enhanced Federated Graph Learning with Geometry-aware Graph Projection and Shared Subspace Aggregation
inferred← citeshttps://doi.org/10.1145/3774904.3792792openalex-snapshot
PI2I: A Personalized Item-Based Collaborative Filtering Retrieval Framework
inferred← citeshttps://doi.org/10.1145/3774934.3786440openalex-snapshot
ElasGNN: An Elastic Training Framework for Distributed GNN Training
inferred← citeshttps://doi.org/10.1145/3774934.3786450openalex-snapshot
APERTURE: Algorithm-System Co-optimization for Temporal Graph Network Inference
inferred← citeshttps://doi.org/10.1145/3775057openalex-snapshot
Global Structure-aware and Feature-augmented Graph Neural Network for Heterophilic Graphs
inferred← citeshttps://doi.org/10.1145/3776568openalex-snapshot
TernaryGNNs: A High-Throughput, Area-Efficient Ternary Weight GNNs Inference Framework on CPU-FPGA Heterogeneous Platform
inferred← citeshttps://doi.org/10.1145/3779212.3790157openalex-snapshot
Efficient Temporal Graph Network Training via Unified Redundancy Elimination
inferred← citeshttps://doi.org/10.1145/3789504openalex-snapshot
Local and Global Contrastive Network for Unsupervised Graph Anomaly Detection
inferred← citeshttps://doi.org/10.1145/3795793openalex-snapshot
D2TCDR: Disentangled Diffusion-Based Transfer for Cross-Domain Recommendation
inferred← citeshttps://doi.org/10.1145/3797905.3800542openalex-snapshot
Rudder: Steering Prefetching in Distributed GNN Training using LLM Agents
inferred← citeshttps://doi.org/10.1145/3805712.3809642openalex-snapshot
DIGEST: Dynamic Graph Refinement with Dual Contrastive Semantic Transfer for Multimodal Recommendation
inferred← citeshttps://doi.org/10.1145/3805712.3809748openalex-snapshot
LLM-EDT: Large Language Models Enhanced Cross-domain Sequential Recommendation with Dual-phase Training
inferred← citeshttps://doi.org/10.1145/3818611openalex-snapshot
Towards Multi-Behavior Multi-Task Recommendation via Behavior-Informed Graph Embedding Learning
inferred← citeshttps://doi.org/10.1145/3821218openalex-snapshot
CurvGCL: Mixed-curvature Manifolds Graph Contrastive Learning for Knowledge-enhanced Recommendation
inferred← citeshttps://doi.org/10.1145/3832810.3832832openalex-snapshot
MServerSim: A Modular Design based Simulation Technique for Modern AI Servers
inferred← citeshttps://doi.org/10.1145/3833876openalex-snapshot
DualPop: User Popularity Preference-Aware Debiasing Recommendation
inferred← citeshttps://doi.org/10.1145/3840748openalex-snapshot
A Survey of Causal Learning in Graph-Based Recommender Systems
inferred← citeshttps://doi.org/10.1145/3846382openalex-snapshot
RecGPT: A User Intent-Centric Next-Generation LLM-Powered Recommender System in Industrial Practice
inferred← citeshttps://doi.org/10.14778/3626292.3626300openalex-snapshot
Billion-Scale Bipartite Graph Embedding: A Global-Local Induced Approach
inferred← citeshttps://doi.org/10.14778/3681954.3681959openalex-snapshot
RoarGraph: A Projected Bipartite Graph for Efficient Cross-Modal Approximate Nearest Neighbor Search
inferred← citeshttps://doi.org/10.14778/3681954.3681975openalex-snapshot
Efficient Maximal Motif-Clique Enumeration over Large Heterogeneous Information Networks
inferred← citeshttps://doi.org/10.14778/3681954.3681976openalex-snapshot
OUTRE: An OUT-of-Core De-REdundancy GNN Training Framework for Massive Graphs within A Single Machine
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