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Machine-Learning

Natural Language Processing
Heatmap visualization of the EigenNoise analytical co-occurrence prior matrix showing word rank relationships

EigenNoise: Data-Free Word Vector Initialization

Investigation into EigenNoise, a data-free initialization scheme for word vectors that approaches pre-trained model …

Computational Social Science
Diagram of the Universal Message schema showing fields like ID, Text, Author, and Reply Sets that normalize data across platforms

PyConversations: Social Media Conversational Analysis

Undergraduate thesis exploring representation learning for social media text and developing tools for cross-platform …

AI Safety
A nonsensical trigger sequence 'WTC theoriesclimate Flat Hubbard Principle' is fed into GPT-2, which then generates Flat Earth conspiracy text

GPT-2 Susceptibility to Universal Adversarial Triggers

Investigation into whether universal adversarial triggers can control both topic and stance of GPT-2's generated text …

Machine Learning Fundamentals
Vintage slot machine with multiple arms representing the multi-arm bandit problem in machine learning

A Framework for Multi-Arm Bandit Problems: 5 Key Dimensions

Framework for understanding multi-arm bandit algorithms through five dimensions. Covers exploration vs exploitation and …

Machine Learning Fundamentals
Various symmetric and repetitive patterns generated by Compositional Pattern Producing Networks

HyperNEAT: Scaling Neuroevolution with Geometric Patterns

How HyperNEAT uses indirect encoding and geometric patterns to evolve large-scale neural networks with biological …

Machine Learning Fundamentals
NEAT genome encoding diagram showing node genes and connection genes with innovation numbers

NEAT: Evolving Neural Network Topologies

Learn about NEAT's approach to evolving neural networks: automatic topology design, historical markings, and speciation …

Machine Learning Fundamentals
Diagram showing the three main types of machine learning: supervised, unsupervised, and reinforcement learning

Breaking Down Machine Learning for the Average Person

Discover how machine learning actually works through three fundamental approaches, explained with everyday examples you …

AI Fundamentals
Diagram showing the relationship between syntax, semantics, inference, and entailment in knowledge-based systems

Fundamentals of Logic: Knowledge Representation

Learn about the foundations of AI logic: syntax, semantics, entailment, and inference algorithms for building …

AI Fundamentals
Diagram illustrating knowledge-based agent architecture with knowledge base, reasoning, and action components

An Introduction to Knowledge-Based Agents

Learn about knowledge-based agents: how AI systems use knowledge bases, reasoning, and inference to build intelligent …

Natural Language Processing
Types and distribution of coreferences in QuAC dataset showing dialogue complexity

QuAC: Question Answering in Context Dataset

Analysis of QuAC's conversational QA through student-teacher interactions, featuring 100K+ context-dependent questions …

Natural Language Processing
Visualization of coreference resolution in the CoQA conversational question answering dataset

CoQA Dataset: Advancing Conversational Question Answering

Analysis of CoQA, a conversational QA dataset with multi-turn dialogue, coreference resolution, and natural answers for …

Generative Modeling
Wasserstein distance visualization showing Earth-Mover distance concept for GAN training

GAN Objective Functions: A Comprehensive Guide

Complete guide to GAN objective functions including WGAN, LSGAN, Fisher GAN, and more. Understand which loss function to …