ML applications

CATS (Contextually Aware Thresholding for Sparsity): A Novel Machine Learning Framework for Inducing and Exploiting Activation Sparsity in LLMs

ML applications

4 Min Read

CATS (Contextually Aware Thresholding for Sparsity): A Novel Machine Learning Framework for Inducing and Exploiting Activation Sparsity in LLMs

By Editorial Team

April 26, 2024

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Neural Flow Diffusion Models (NFDM): A Novel Machine Learning Framework that Enhances Diffusion Models by Supporting a Broader Range of Forward Processes Beyond the Fixed Linear Gaussian

ML applications

4 Min Read

Neural Flow Diffusion Models (NFDM): A Novel Machine Learning Framework that Enhances Diffusion Models by Supporting a Broader Range of Forward Processes Beyond the Fixed Linear Gaussian

By Editorial Team

April 26, 2024

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Researchers at ServiceNow Propose a Machine Learning Approach to Deploy a Retrieval Augmented LLM to Reduce Hallucination and Allow Generalization in a Structured Output Task

ML applications

4 Min Read

Researchers at ServiceNow Propose a Machine Learning Approach to Deploy a Retrieval Augmented LLM to Reduce Hallucination and Allow Generalization in a Structured Output Task

By Editorial Team

April 25, 2024

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Researchers at MIT Propose ‘MAIA’: An Artificial Intelligence System that Uses Neural Network Models to Automate Neural Model Understanding Tasks

ML applications

3 Min Read

Researchers at MIT Propose ‘MAIA’: An Artificial Intelligence System that Uses Neural Network Models to Automate Neural Model Understanding Tasks

By Editorial Team

April 25, 2024

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JP Morgan AI Research Introduces FlowMind: A Novel Machine Learning Approach that Leverages the Capabilities of LLMs such as GPT to Create an Automatic Workflow Generation System

ML applications

4 Min Read

JP Morgan AI Research Introduces FlowMind: A Novel Machine Learning Approach that Leverages the Capabilities of LLMs such as GPT to Create an Automatic Workflow Generation System

By Editorial Team

April 25, 2024

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Interpretable Deep Learning for Biodiversity Monitoring: Introducing AudioProtoPNet

ML applications

3 Min Read

Interpretable Deep Learning for Biodiversity Monitoring: Introducing AudioProtoPNet

By Editorial Team

April 24, 2024

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VDTuner: A Machine Learning-Based Automatic Performance Tuning Framework for Vector Data Management Systems (VDMSs)

ML applications

3 Min Read

VDTuner: A Machine Learning-Based Automatic Performance Tuning Framework for Vector Data Management Systems (VDMSs)

By Editorial Team

April 24, 2024

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KDk: A Novel Machine Learning Framework that Protects Vertical Federated Learning from All the Known Types of Label Inference Attacks with Very High Performance

ML applications

3 Min Read

KDk: A Novel Machine Learning Framework that Protects Vertical Federated Learning from All the Known Types of Label Inference Attacks with Very High Performance

By Editorial Team

April 24, 2024

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Privacy-Preserving Training-as-a-Service (PTaaS): A Novel Service Computing Paradigm that Provides Privacy-Friendly and Customized Machine Learning Model Training for End Devices

ML applications

3 Min Read

Privacy-Preserving Training-as-a-Service (PTaaS): A Novel Service Computing Paradigm that Provides Privacy-Friendly and Customized Machine Learning Model Training for End Devices

By Editorial Team

April 24, 2024

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This AI Paper Proposes a Novel Bayesian Deep Learning Model with Kernel Dropout Designed to Enhance the Reliability of Predictions in Medical Text Classification Tasks

ML applications

4 Min Read

This AI Paper Proposes a Novel Bayesian Deep Learning Model with Kernel Dropout Designed to Enhance the Reliability of Predictions in Medical Text Classification Tasks

By Editorial Team

April 24, 2024

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ML applications

CATS (Contextually Aware Thresholding for Sparsity): A Novel Machine Learning Framework for Inducing and Exploiting Activation Sparsity in LLMs

Neural Flow Diffusion Models (NFDM): A Novel Machine Learning Framework that Enhances Diffusion Models by Supporting a Broader Range of Forward Processes Beyond the Fixed Linear Gaussian

Researchers at ServiceNow Propose a Machine Learning Approach to Deploy a Retrieval Augmented LLM to Reduce Hallucination and Allow Generalization in a Structured Output Task

Researchers at MIT Propose ‘MAIA’: An Artificial Intelligence System that Uses Neural Network Models to Automate Neural Model Understanding Tasks

JP Morgan AI Research Introduces FlowMind: A Novel Machine Learning Approach that Leverages the Capabilities of LLMs such as GPT to Create an Automatic Workflow Generation System

Interpretable Deep Learning for Biodiversity Monitoring: Introducing AudioProtoPNet

VDTuner: A Machine Learning-Based Automatic Performance Tuning Framework for Vector Data Management Systems (VDMSs)

KDk: A Novel Machine Learning Framework that Protects Vertical Federated Learning from All the Known Types of Label Inference Attacks with Very High Performance

Privacy-Preserving Training-as-a-Service (PTaaS): A Novel Service Computing Paradigm that Provides Privacy-Friendly and Customized Machine Learning Model Training for End Devices

This AI Paper Proposes a Novel Bayesian Deep Learning Model with Kernel Dropout Designed to Enhance the Reliability of Predictions in Medical Text Classification Tasks

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