Papers Mathematical Induction
“Mathematical Induction” 태그가 달린 논문 12편 · 필터 해제
MiMuon: Mixed Muon Optimizer with Improved Generalization for Large Models
Matrix-structured parameters frequently appear in many artificial intelligence models such as large language models. More recently, an efficient Muon optimizer is designed for matrix parameters of large-scale models, and…
Mathematical InductionCLion: Efficient Cautious Lion Optimizer with Enhanced Generalization
Lion optimizer is a popular learning-based optimization algorithm in machine learning, which shows impressive performance in training many deep learning models. Although convergence property of the Lion optimizer has bee…
Stochastic OptimizationMathematical InductionTransient Error Analysis of the LMS and RLS Algorithm for Graph Signal Estimation
Recently, the proposal of the least mean square (LMS) and recursive least squares (RLS) algorithm for graph signal processing (GSP) provides excellent solutions for processing signals defined on irregular structures such…
Mathematical InductionDynamic Logistic Ensembles with Recursive Probability and Automatic Subset Splitting for Enhanced Binary Classification
This paper presents a novel approach to binary classification using dynamic logistic ensemble models. The proposed method addresses the challenges posed by datasets containing inherent internal clusters that lack explici…
Binary ClassificationComputational EfficiencyMathematical InductionA Unified Analysis for Finite Weight Averaging
Averaging iterations of Stochastic Gradient Descent (SGD) have achieved empirical success in training deep learning models, such as Stochastic Weight Averaging (SWA), Exponential Moving Average (EMA), and LAtest Weight A…
Mathematical InductionAutograding Mathematical Induction Proofs with Natural Language Processing
In mathematical proof education, there remains a need for interventions that help students learn to write mathematical proofs. Research has shown that timely feedback can be very helpful to students learning new skills. …
Mathematical InductionMathematical ProofsSNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training
In an era where symbolic mathematical equations are indispensable for modeling complex natural phenomena, scientific inquiry often involves collecting observations and translating them into mathematical expressions. Rece…
Contrastive LearningEquation DiscoveryFew-Shot LearningMath+4Analysis of function approximation and stability of general DNNs in directed acyclic graphs using un-rectifying analysis
A general lack of understanding pertaining to deep feedforward neural networks (DNNs) can be attributed partly to a lack of tools with which to analyze the composition of non-linear functions, and partly to a lack of mat…
DiversityMathematical InductionTraining Compute-Optimal Large Language Models
We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget. We find that current large language models are significantly undertrained, a consequence …
AnachronismsAnalogical SimilarityAnalytic EntailmentCausal Judgment+69Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world. In this paper, we present an analysis o…
Abstract AlgebraAnachronismsAnalogical SimilarityAnalytic Entailment+143Derivation of the Backpropagation Algorithm Based on Derivative Amplification Coefficients
The backpropagation algorithm for neural networks is widely felt hard to understand, despite the existence of some well-written explanations and/or derivations. This paper provides a new derivation of this algorithm base…
Mathematical InductionAutomation of Mathematical Induction as part of the History of Logic
We review the history of the automation of mathematical induction
Mathematical Induction