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Machine Learning

A branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.

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SVM and Kernels: The Math that Makes Classification Magic
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SVM and Kernels: The Math that Makes Classification Magic

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3 min read
AI and Collaborative Robots Shape Tomorrow's Workforce
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AI and Collaborative Robots Shape Tomorrow's Workforce

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3 min read
TrustScore: Reference-Free Evaluation of LLM Response Trustworthiness
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TrustScore: Reference-Free Evaluation of LLM Response Trustworthiness

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3 min read
CascadedGaze: Efficiency in Global Context Extraction for Image Restoration
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CascadedGaze: Efficiency in Global Context Extraction for Image Restoration

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3 min read
Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents
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Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents

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4 min read
AlphaMath Almost Zero: process Supervision without process
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AlphaMath Almost Zero: process Supervision without process

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4 min read
Trustworthy AI: Navigating the Ethical Challenges of AI Deployment and Decision-Making

Trustworthy AI: Navigating the Ethical Challenges of AI Deployment and Decision-Making

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2 min read
LeT's CoNtRoL YoU tO HeLp Me

LeT's CoNtRoL YoU tO HeLp Me

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1 min read
Prompt Design and Engineering: Introduction and Advanced Methods
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Prompt Design and Engineering: Introduction and Advanced Methods

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4 min read
SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking

SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking

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4 min read
Generative AI Beyond LLMs: System Implications of Multi-Modal Generation
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Generative AI Beyond LLMs: System Implications of Multi-Modal Generation

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3 min read
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity
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Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity

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4 min read
A Simple and Effective Pruning Approach for Large Language Models
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A Simple and Effective Pruning Approach for Large Language Models

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3 min read
R-Tuning: Instructing Large Language Models to Say `I Don't Know'

R-Tuning: Instructing Large Language Models to Say `I Don't Know'

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4 min read
SAR image matching algorithm based on multi-class features

SAR image matching algorithm based on multi-class features

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4 min read
PopulAtion Parameter Averaging (PAPA)

PopulAtion Parameter Averaging (PAPA)

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3 min read
Porting HPC Applications to AMD Instinct$^text{TM}$ MI300A Using Unified Memory and OpenMP

Porting HPC Applications to AMD Instinct$^text{TM}$ MI300A Using Unified Memory and OpenMP

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4 min read
Network reconstruction via the minimum description length principle
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Network reconstruction via the minimum description length principle

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3 min read
Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks

Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks

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4 min read
Are aligned neural networks adversarially aligned?
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Are aligned neural networks adversarially aligned?

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4 min read
Poisoning Web-Scale Training Datasets is Practical

Poisoning Web-Scale Training Datasets is Practical

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3 min read
Circuit Component Reuse Across Tasks in Transformer Language Models
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Circuit Component Reuse Across Tasks in Transformer Language Models

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4 min read
Beyond Memorization: Violating Privacy Via Inference with Large Language Models

Beyond Memorization: Violating Privacy Via Inference with Large Language Models

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3 min read
FLAME: Factuality-Aware Alignment for Large Language Models

FLAME: Factuality-Aware Alignment for Large Language Models

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4 min read
ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing

ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing

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3 min read
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