Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems.
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VLDB J., September, 2024
TQA-Bench: Evaluating LLMs for Multi-Table Question Answering with Scalable Context and Symbolic Extension.
CoRR, 2024
Zero-Indexing Internet Search Augmented Generation for Large Language Models.
CoRR, 2024
Multi-Agent Collaborative Data Selection for Efficient LLM Pretraining.
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CoRR, 2024
Locret: Enhancing Eviction in Long-Context LLM Inference with Trained Retaining Heads.
CoRR, 2024
FlashFlex: Accommodating Large Language Model Training over Heterogeneous Environment.
CoRR, 2024
On the Opportunities of (Re)-Exploring Atmospheric Science by Foundation Models: A Case Study.
CoRR, 2024
A Survey of Multimodal Large Language Model from A Data-centric Perspective.
CoRR, 2024
Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model.
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CoRR, 2024
DeFT: Flash Tree-attention with IO-Awareness for Efficient Tree-search-based LLM Inference.
CoRR, 2024
Adding NVMe SSDs to Enable and Accelerate 100B Model Fine-tuning on a Single GPU.
CoRR, 2024
CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference.
CoRR, 2024
Model-GLUE: Democratized LLM Scaling for A Large Model Zoo in the Wild.
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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
HexGen: Generative Inference of Large Language Model over Heterogeneous Environment.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Serving Deep Learning Models from Relational Databases.
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Proceedings of the Proceedings 27th International Conference on Extending Database Technology, 2024
Exploring the Robustness of Decentralized Training for Large Language Models.
CoRR, 2023
HexGen: Generative Inference of Foundation Model over Heterogeneous Decentralized Environment.
CoRR, 2023
Serving Deep Learning Model in Relational Databases.
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CoRR, 2023
High-throughput Generative Inference of Large Language Models with a Single GPU.
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CoRR, 2023
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks.
Proceedings of the International Conference on Machine Learning, 2023
Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning.
Proceedings of the International Conference on Machine Learning, 2023
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time.
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Proceedings of the International Conference on Machine Learning, 2023
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU.
Proceedings of the International Conference on Machine Learning, 2023
Bayesian Hierarchical Model for Change Point Detection in Multivariate Sequences.
Technometrics, 2022
Distributed Learning of Fully Connected Neural Networks using Independent Subnet Training.
Proc. VLDB Endow., 2022
A community effort to assess and improve computerized interpretation of 12-lead resting electrocardiogram.
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Medical Biol. Eng. Comput., 2022
Stochastic Gradient Descent without Full Data Shuffle.
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CoRR, 2022
Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees.
CoRR, 2022
In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle.
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Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022
Decentralized Training of Foundation Models in Heterogeneous Environments.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters.
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Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Efficient flow scheduling in distributed deep learning training with echelon formation.
Proceedings of the 21st ACM Workshop on Hot Topics in Networks, 2022
A Feature Fusion Framework and Its Application to Automatic Seizure Detection.
IEEE Signal Process. Lett., 2021
Lachesis: Automated Partitioning for UDF-Centric Analytics.
Proc. VLDB Endow., 2021
Tensor Relational Algebra for Distributed Machine Learning System Design.
Proc. VLDB Endow., 2021
Distributed Numerical and Machine Learning Computations via Two-Phase Execution of Aggregated Join Trees.
Proc. VLDB Endow., 2021
BAGUA: Scaling up Distributed Learning with System Relaxations.
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Proc. VLDB Endow., 2021
Automatic Optimization of Matrix Implementations for Distributed Machine Learning and Linear Algebra.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021
Declarative Recursive Computation on an RDBMS: or, Why You Should Use a Database For Distributed Machine Learning.
SIGMOD Rec., 2020
Tensor Relational Algebra for Machine Learning System Design.
CoRR, 2020
Lachesis: Automated Generation of Persistent Partitionings for Big Data Applications.
CoRR, 2020
A Federated Learning Framework for Healthcare IoT devices.
CoRR, 2020
Declarative Recursive Computation on an RDBMS.
Proc. VLDB Endow., 2019
Distributed Learning of Deep Neural Networks using Independent Subnet Training.
CoRR, 2019
WaveletFCNN: A Deep Time Series Classification Model for Wind Turbine Blade Icing Detection.
CoRR, 2019
Diagnosing Cardiac Abnormalities from 12-Lead Electrocardiograms Using Enhanced Deep Convolutional Neural Networks.
Proceedings of the Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting, 2019
PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development.
Proceedings of the 2018 International Conference on Management of Data, 2018
Proc. ACM Program. Lang., 2017
Generating a 3D Normative Infant Cranial Model.
Proceedings of the International Conference on Computational Science 2016, 2016
Effective Video Retargeting With Jittery Assessment.
IEEE Trans. Multim., 2014