FlashPS: Efficient Generative Image Editing with Mask-aware Caching and Scheduling

ChatCAD: An MLLM-Guided Framework for Zero-shot CAD Drawing Restoration

FedPHE: A Secure and Efficient Federated Learning via Packed Homomorphic Encryption

Guest Editorial Special Issue on Federated Learning for Big Data Applications

Parameter estimation of structural dynamics with neural operators enabled surrogate modeling

Pheromone: Restructuring Serverless Computing With Data-Centric Function Orchestration

SP-Chain: Boosting Intrashard and Cross-Shard Security and Performance in Blockchain Sharding

Structural Clustering for Bipartite Graphs

Top Ten Challenges Towards Agentic Neural Graph Databases

BRIDGING AND MODELING CORRELATIONS IN PAIRWISE DATA FOR DIRECT PREFERENCE OPTIMIZATION

Effective and General Distance Computation for Approximate Nearest Neighbor Search

GPU-Disaggregated Serving for Deep Learning Recommendation Models at Scale

Harnessing Scale and Physics: A Multi-Graph Neural Operator Framework for PDEs on Arbitrary Geometries

INFLUENCE-GUIDED DIFFUSION FOR DATASET DISTILLATION

KATZ: Efficient Workflow Serving for Diffusion Models with Many Adapters

Locally Balancing Signed Graphs

Optimizing Distributed Deployment of Mixture-of-Experts Model Inference in Serverless Computing

Private Realizable-to-Agnostic Transformation with Near-Optimal Sample Complexity

Low-Contrast Medical Image Segmentation via Transformer and Boundary Perception

MorphDAG: A Workload-Aware Elastic DAG-Based Blockchain

Self-Supervised Feature Learning for Appliance Recognition in Nonintrusive Load Monitoring

Synchronize Only the Immature Parameters: Communication-Efficient Federated Learning By Freezing Parameters Adaptively

Towards Efficient and Deposit-Free Blockchain-Based Spatial Crowdsourcing

Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy

DTC-SpMM: Bridging the Gap in Accelerating General Sparse Matrix Multiplication with Tensor Cores

SAFE: Intelligent Online Scheduling for Collaborative DNN Inference in Vehicular Network

A deep neural network for general scattering matrix

Accelerating Distributed Learning in Non-Dedicated Environments

Deep Learning for Approximate Nearest Neighbour Search: A Survey and Future Directions

DifFormer: Multi-Resolutional Differencing Transformer With Dynamic Ranging for Time Series Analysis

Expanding Reverse Nearest Neighbors

GIFT: Toward Accurate and Efficient Federated Learning With Gradient-Instructed Frequency Tuning

LB-Chain: Load-Balanced and Low-Latency Blockchain Sharding via Account Migration

LMSFC: A Novel Multidimensional Index Based on Learned Monotonic Space Filling Curves

Monocular 3-D Object Detection Based on Depth-Guided Local Convolution for Smart Payment in D2D Systems

Scalable K-FAC Training for Deep Neural Networks with Distributed Preconditioning

Towards Efficient Synchronous Federated Training: A Survey on System Optimization Strategies

Unbiased quasi-hyperbolic nesterov-gradient momentum-based optimizers for accelerating convergence

Beware of Fragmentation: Scheduling GPU-Sharing Workloads with Fragmentation Gradient Descent

Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation

Cardinality Estimation of Subgraph Search Queries with Direction Learner

CoChain: High Concurrency Blockchain Sharding via Consensus on Consensus

CoSaR: Combating Label Noise Using Collaborative Sample Selection and Adversarial Regularization

DeAR: Accelerating Distributed Deep Learning with Fine-Grained All-Reduce Pipelining

Distance Maximization and Defences on Deep Hashing Based Image Retrieval

Fast Sparse GPU Kernels for Accelerated Training of Graph Neural Networks

Following the Data, Not the Function: Rethinking Function Orchestration in Serverless Computing

Global and Local Hierarchy-aware Contrastive Framework for Implicit Discourse Relation Recognition

Golgi: Performance-Aware, Resource-Efficient Function Scheduling for Serverless Computing

Graph Self-supervised Learning with Augmentation-aware Contrastive Learning

Lion: Adversarial Distillation of Proprietary Large Language Models

UG-Net: Corneal Endothelial Cell Segmentation Based on Uncertainty Estimation and Soft Spatial Attention

A home energy management system incorporating data-driven uncertainty-aware user preference

A Single-to-Multi Network for Latency-Free Non-Intrusive Load Monitoring

Data predictive control of nonlinear process feature dynamics through latent variable behaviours

Editorial: Advances in Mobile, Edge and Cloud Computing

Enabling Cost-Effective, SLO-Aware Machine Learning Inference Serving on Public Cloud

GCP: Graph Encoder with Content-Planning for Sentence Generation from Knowledge Bases

Incentivizing WiFi-Based Multilateration Location Verification

On entity alignment at scale

Towards Dependency-Aware Cache Management for Data Analytics Applications

群体智能中的联邦学习算法综述

Costly Price Adjustment and Automated Pricing: The Case of Airbnb: An Abstract

Jenga: Orchestrating Smart Contracts in Sharding-Based Blockchain for Efficient Processing

MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction

MLaaS in the Wild: Workload Analysis and Scheduling in Large-Scale Heterogeneous GPU Clusters

Neural Subgraph Counting with Wasserstein Estimator

Owl: Performance-Aware Scheduling for Resource-Efficient Function-as-a-Service Cloud

Pisces: Efficient Federated Learning via Guided Asynchronous Training

POSTER: An LLVM-based Open-Source Compiler for NVIDIA GPUs

Reinforcement Learning Based Query Vertex Ordering Model for Subgraph Matching

Software-defined network assimilation: Bridging the last mile towards centralized network configuration management with nassim

Workload Consolidation in Alibaba Clusters: The Good, the Bad, and the Ugly

A Quantitative Survey of Communication Optimizations in Distributed Deep Learning

Guest Editorial: Interplay between Machine Learning and Networking Systems

Toward Privacy-Preserving Task Assignment for Fully Distributed Spatial Crowdsourcing

A smart adversarial attack on deep hashing based image retrieval

Citadel: Protecting data privacy and model confidentiality for collaborative learning

Communication-efficient federated learning with adaptive parameter freezing

CrystalPerf: Learning to characterize the performance of dataflow computation through code analysis

George: Learning to place long-lived containers in large clusters with operation constraints

Gillis: Serving large neural networks in serverless functions with automatic model partitioning

High-Dimensional Similarity Query Processing for Data Science

KS-GNN: Keywords Search over Incomplete Graphs via Graph Neural Network

Morphling: Fast, near-optimal auto-configuration for cloud-native model serving

Relation Prediction via Graph Neural Network in Heterogeneous Information Networks with Missing Type Information

Sent2Span: Span Detection for PICO Extraction in the Biomedical Text without Span Annotations

Simplifying low-level GPU programming with GAS

Achieving Load-Balanced, Redundancy-Free Cluster Caching with Selective Partition

BatchCrypt: Efficient homomorphic encryption for cross-silo federated learning

Demystifying Tensor Cores to Optimize Half-Precision Matrix Multiply

Metis: Learning to schedule long-running applications in shared container clusters at scale

Not All Explorations Are Equal: Harnessing Heterogeneous Profiling Cost for Efficient MLaaS Training

Optimizing batched winograd convolution on GPUs

RepBun: Load-Balanced, Shuffle-Free Cluster Caching for Structured Data

Semi-dynamic load balancing: Efficient distributed learning in non-dedicated environments

Abnormal Client Behavior Detection in Federated Learning

Characterizing and Synthesizing Task Dependencies of Data-Parallel Jobs in Alibaba Cloud

CMFL: Mitigating communication overhead for federated learning

LACS: Load-aware cache sharing with isolation guarantee

Mark: Exploiting cloud services for cost-effective, slo-aware machine learning inference serving

Round-Robin Synchronization: Mitigating Communication Bottlenecks in Parameter Servers

Towards framework-independent, non-intrusive performance characterization for dataflow computation

Task Selection and Scheduling for Food Delivery: A Game-Theoretic Approach

Unraveling the RTT-fairness Problem for BBR: A Queueing Model

Continuum: A platform for cost-aware, low-latency continual learning

Fair coflow scheduling without prior knowledge

Fast distributed deep learning via worker-adaptive batch sizing

OpuS: Fair and efficient cache sharing for in-memory data analytics

Performance-Aware Fair Scheduling: Exploiting Demand Elasticity of Data Analytics Jobs

SP-cache: Load-balanced, redundancy-free cluster caching with selective partition

Stay fresh: Speculative synchronization for fast distributed machine learning

Utopia: Near-optimal Coflow Scheduling with Isolation Guarantee

LERC: Coordinated cache management for data-parallel systems

Towards Online Checkpointing Mechanism for Cloud Transient Servers

Cluster fair queueing: Speeding up data-parallel jobs with delay guarantees

Coflex: Navigating the fairness-efficiency tradeoff for coflow scheduling

LRC: Dependency-aware cache management for data analytics clusters

Speculative Slot Reservation: Enforcing Service Isolation for Dependent Data-Parallel Computations

Friends or foes: Revisiting strategy-proofness in cloud network sharing

Multi-resource Fair Sharing for Datacenter Jobs with Placement Constraints

Dynamic cloud instance acquisition via IaaS cloud brokerage

Multi-Resource Fair Allocation in Heterogeneous Cloud Computing Systems

Optimal Online Multi-Instance Acquisition in IaaS Clouds

Designing truthful spectrum double auctions with local markets

Local cooperation architecture for self-healing femtocell networks

Dominant resource fairness in cloud computing systems with heterogeneous servers

Low complexity multi-resource fair queueing with bounded delay

On the fairness-Efficiency tradeoff for packet processing with multiple resources

Multi-resource generalized processor sharing for packet processing

Revenue maximization with dynamic auctions in IaaS cloud markets

Dynamic cloud resource reservation via cloud brokerage

Multi-resource round robin: A low complexity packet scheduler with dominant resource fairness

On fairness-efficiency tradeoffs for multi-resource packet processing

To Reserve or Not to Reserve: Optimal Online Multi-Instance Acquisition in IaaS Clouds

Towards optimal capacity segmentation with hybrid cloud pricing

District: Embracing local markets in truthful spectrum double auctions

Achieving Load-Balanced, Redundancy-Free Cluster Caching with Selective Partition

Article

BatchCrypt: Efficient homomorphic encryption for cross-silo federated learning

Conference paper

Demystifying Tensor Cores to Optimize Half-Precision Matrix Multiply

Conference paper

Metis: Learning to schedule long-running applications in shared container clusters at scale

Conference paper

Not All Explorations Are Equal: Harnessing Heterogeneous Profiling Cost for Efficient MLaaS Training

Conference paper

Optimizing batched winograd convolution on GPUs

Conference paper

RepBun: Load-Balanced, Shuffle-Free Cluster Caching for Structured Data

Conference paper

Semi-dynamic load balancing: Efficient distributed learning in non-dedicated environments

Conference paper

Abnormal Client Behavior Detection in Federated Learning

Conference paper

Characterizing and Synthesizing Task Dependencies of Data-Parallel Jobs in Alibaba Cloud

Conference paper

CMFL: Mitigating communication overhead for federated learning

Conference paper

LACS: Load-aware cache sharing with isolation guarantee

Conference paper

Mark: Exploiting cloud services for cost-effective, slo-aware machine learning inference serving

Conference paper

Round-Robin Synchronization: Mitigating Communication Bottlenecks in Parameter Servers

Conference paper

Towards framework-independent, non-intrusive performance characterization for dataflow computation

Conference paper

Task Selection and Scheduling for Food Delivery: A Game-Theoretic Approach

Article

Unraveling the RTT-fairness Problem for BBR: A Queueing Model

Article

Continuum: A platform for cost-aware, low-latency continual learning

Conference paper

Fair coflow scheduling without prior knowledge

Conference paper

Fast distributed deep learning via worker-adaptive batch sizing

Conference paper

OpuS: Fair and efficient cache sharing for in-memory data analytics

Conference paper

Performance-Aware Fair Scheduling: Exploiting Demand Elasticity of Data Analytics Jobs

Conference paper

SP-cache: Load-balanced, redundancy-free cluster caching with selective partition

Conference paper

Stay fresh: Speculative synchronization for fast distributed machine learning

Conference paper

Utopia: Near-optimal Coflow Scheduling with Isolation Guarantee

Conference paper

LERC: Coordinated cache management for data-parallel systems

Article

Towards Online Checkpointing Mechanism for Cloud Transient Servers

Article

Cluster fair queueing: Speeding up data-parallel jobs with delay guarantees

Conference paper

Coflex: Navigating the fairness-efficiency tradeoff for coflow scheduling

Conference paper

LRC: Dependency-aware cache management for data analytics clusters

Conference paper

Speculative Slot Reservation: Enforcing Service Isolation for Dependent Data-Parallel Computations

Conference paper

Friends or foes: Revisiting strategy-proofness in cloud network sharing

Conference paper

Multi-resource Fair Sharing for Datacenter Jobs with Placement Constraints

Conference paper

Dynamic cloud instance acquisition via IaaS cloud brokerage

Article

Multi-Resource Fair Allocation in Heterogeneous Cloud Computing Systems

Article

Optimal Online Multi-Instance Acquisition in IaaS Clouds

Article

Designing truthful spectrum double auctions with local markets

Article

Local cooperation architecture for self-healing femtocell networks

Article

Dominant resource fairness in cloud computing systems with heterogeneous servers

Conference paper

Low complexity multi-resource fair queueing with bounded delay

Conference paper

On the fairness-Efficiency tradeoff for packet processing with multiple resources

Conference paper

Multi-resource generalized processor sharing for packet processing

Article

Revenue maximization with dynamic auctions in IaaS cloud markets

Article

Dynamic cloud resource reservation via cloud brokerage

Conference paper

Multi-resource round robin: A low complexity packet scheduler with dominant resource fairness

Conference paper

On fairness-efficiency tradeoffs for multi-resource packet processing

Conference paper

To Reserve or Not to Reserve: Optimal Online Multi-Instance Acquisition in IaaS Clouds

Conference paper

Towards optimal capacity segmentation with hybrid cloud pricing

Conference paper

District: Embracing local markets in truthful spectrum double auctions

Conference paper