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Machine Learning

[D] ICML reviewer making up false claim in acknowledgement, what to do?

In a rebuttal acknowledgement we received, the reviewer made up a claim that our method performs worse than baselines with some hyperpara...

Reddit - Machine Learning · 1 min ·
UMKC Announces New Master of Science in Artificial Intelligence
Ai Infrastructure

UMKC Announces New Master of Science in Artificial Intelligence

UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...

AI News - General · 4 min ·
Machine Learning

[D] Budget Machine Learning Hardware

Looking to get into machine learning and found this video on a piece of hardware for less than £500. Is it really possible to teach auton...

Reddit - Machine Learning · 1 min ·

All Content

[2603.24518] TuneShift-KD: Knowledge Distillation and Transfer for Fine-tuned Models
Llms

[2603.24518] TuneShift-KD: Knowledge Distillation and Transfer for Fine-tuned Models

Abstract page for arXiv paper 2603.24518: TuneShift-KD: Knowledge Distillation and Transfer for Fine-tuned Models

arXiv - Machine Learning · 4 min ·
[2603.24517] AVO: Agentic Variation Operators for Autonomous Evolutionary Search
Llms

[2603.24517] AVO: Agentic Variation Operators for Autonomous Evolutionary Search

Abstract page for arXiv paper 2603.24517: AVO: Agentic Variation Operators for Autonomous Evolutionary Search

arXiv - Machine Learning · 4 min ·
[2603.24503] Towards Safe Learning-Based Non-Linear Model Predictive Control through Recurrent Neural Network Modeling
Machine Learning

[2603.24503] Towards Safe Learning-Based Non-Linear Model Predictive Control through Recurrent Neural Network Modeling

Abstract page for arXiv paper 2603.24503: Towards Safe Learning-Based Non-Linear Model Predictive Control through Recurrent Neural Networ...

arXiv - Machine Learning · 3 min ·
[2603.24500] Project and Generate: Divergence-Free Neural Operators for Incompressible Flows
Machine Learning

[2603.24500] Project and Generate: Divergence-Free Neural Operators for Incompressible Flows

Abstract page for arXiv paper 2603.24500: Project and Generate: Divergence-Free Neural Operators for Incompressible Flows

arXiv - Machine Learning · 3 min ·
[2603.24475] Conformalized Transfer Learning for Li-ion Battery State of Health Forecasting under Manufacturing and Usage Variability
Machine Learning

[2603.24475] Conformalized Transfer Learning for Li-ion Battery State of Health Forecasting under Manufacturing and Usage Variability

Abstract page for arXiv paper 2603.24475: Conformalized Transfer Learning for Li-ion Battery State of Health Forecasting under Manufactur...

arXiv - Machine Learning · 3 min ·
[2603.24431] Learning Response-Statistic Shifts and Parametric Roll Episodes from Wave--Vessel Time Series via LSTM Functional Models
Machine Learning

[2603.24431] Learning Response-Statistic Shifts and Parametric Roll Episodes from Wave--Vessel Time Series via LSTM Functional Models

Abstract page for arXiv paper 2603.24431: Learning Response-Statistic Shifts and Parametric Roll Episodes from Wave--Vessel Time Series v...

arXiv - Machine Learning · 4 min ·
[2603.24428] Marchuk: Efficient Global Weather Forecasting from Mid-Range to Sub-Seasonal Scales via Flow Matching
Machine Learning

[2603.24428] Marchuk: Efficient Global Weather Forecasting from Mid-Range to Sub-Seasonal Scales via Flow Matching

Abstract page for arXiv paper 2603.24428: Marchuk: Efficient Global Weather Forecasting from Mid-Range to Sub-Seasonal Scales via Flow Ma...

arXiv - Machine Learning · 4 min ·
[2603.24384] On the Use of Bagging for Local Intrinsic Dimensionality Estimation
Machine Learning

[2603.24384] On the Use of Bagging for Local Intrinsic Dimensionality Estimation

Abstract page for arXiv paper 2603.24384: On the Use of Bagging for Local Intrinsic Dimensionality Estimation

arXiv - Machine Learning · 4 min ·
[2603.24382] MolEvolve: LLM-Guided Evolutionary Search for Interpretable Molecular Optimization
Llms

[2603.24382] MolEvolve: LLM-Guided Evolutionary Search for Interpretable Molecular Optimization

Abstract page for arXiv paper 2603.24382: MolEvolve: LLM-Guided Evolutionary Search for Interpretable Molecular Optimization

arXiv - Machine Learning · 3 min ·
[2603.24324] Large Language Model Guided Incentive Aware Reward Design for Cooperative Multi-Agent Reinforcement Learning
Llms

[2603.24324] Large Language Model Guided Incentive Aware Reward Design for Cooperative Multi-Agent Reinforcement Learning

Abstract page for arXiv paper 2603.24324: Large Language Model Guided Incentive Aware Reward Design for Cooperative Multi-Agent Reinforce...

arXiv - AI · 4 min ·
[2603.24275] Language-Assisted Image Clustering Guided by Discriminative Relational Signals and Adaptive Semantic Centers
Llms

[2603.24275] Language-Assisted Image Clustering Guided by Discriminative Relational Signals and Adaptive Semantic Centers

Abstract page for arXiv paper 2603.24275: Language-Assisted Image Clustering Guided by Discriminative Relational Signals and Adaptive Sem...

arXiv - Machine Learning · 3 min ·
[2603.24254] Embracing Heteroscedasticity for Probabilistic Time Series Forecasting
Machine Learning

[2603.24254] Embracing Heteroscedasticity for Probabilistic Time Series Forecasting

Abstract page for arXiv paper 2603.24254: Embracing Heteroscedasticity for Probabilistic Time Series Forecasting

arXiv - Machine Learning · 3 min ·
[2603.24265] DeepDTF: Dual-Branch Transformer Fusion for Multi-Omics Anticancer Drug Response Prediction
Machine Learning

[2603.24265] DeepDTF: Dual-Branch Transformer Fusion for Multi-Omics Anticancer Drug Response Prediction

Abstract page for arXiv paper 2603.24265: DeepDTF: Dual-Branch Transformer Fusion for Multi-Omics Anticancer Drug Response Prediction

arXiv - Machine Learning · 4 min ·
[2603.24262] Forecasting with Guidance: Representation-Level Supervision for Time Series Forecasting
Machine Learning

[2603.24262] Forecasting with Guidance: Representation-Level Supervision for Time Series Forecasting

Abstract page for arXiv paper 2603.24262: Forecasting with Guidance: Representation-Level Supervision for Time Series Forecasting

arXiv - Machine Learning · 3 min ·
[2603.24232] Attack Assessment and Augmented Identity Recognition for Human Skeleton Data
Machine Learning

[2603.24232] Attack Assessment and Augmented Identity Recognition for Human Skeleton Data

Abstract page for arXiv paper 2603.24232: Attack Assessment and Augmented Identity Recognition for Human Skeleton Data

arXiv - Machine Learning · 4 min ·
[2603.24213] Uncovering Memorization in Timeseries Imputation models: LBRM Membership Inference and its link to attribute Leakage
Machine Learning

[2603.24213] Uncovering Memorization in Timeseries Imputation models: LBRM Membership Inference and its link to attribute Leakage

Abstract page for arXiv paper 2603.24213: Uncovering Memorization in Timeseries Imputation models: LBRM Membership Inference and its link...

arXiv - Machine Learning · 4 min ·
[2603.24207] IPatch: A Multi-Resolution Transformer Architecture for Robust Time-Series Forecasting
Machine Learning

[2603.24207] IPatch: A Multi-Resolution Transformer Architecture for Robust Time-Series Forecasting

Abstract page for arXiv paper 2603.24207: IPatch: A Multi-Resolution Transformer Architecture for Robust Time-Series Forecasting

arXiv - Machine Learning · 3 min ·
[2603.24202] A Deep Dive into Scaling RL for Code Generation with Synthetic Data and Curricula
Llms

[2603.24202] A Deep Dive into Scaling RL for Code Generation with Synthetic Data and Curricula

Abstract page for arXiv paper 2603.24202: A Deep Dive into Scaling RL for Code Generation with Synthetic Data and Curricula

arXiv - Machine Learning · 4 min ·
[2603.24186] TsetlinWiSARD: On-Chip Training of Weightless Neural Networks using Tsetlin Automata on FPGAs
Machine Learning

[2603.24186] TsetlinWiSARD: On-Chip Training of Weightless Neural Networks using Tsetlin Automata on FPGAs

Abstract page for arXiv paper 2603.24186: TsetlinWiSARD: On-Chip Training of Weightless Neural Networks using Tsetlin Automata on FPGAs

arXiv - Machine Learning · 4 min ·
[2603.24143] Linear-Nonlinear Fusion Neural Operator for Partial Differential Equations
Machine Learning

[2603.24143] Linear-Nonlinear Fusion Neural Operator for Partial Differential Equations

Abstract page for arXiv paper 2603.24143: Linear-Nonlinear Fusion Neural Operator for Partial Differential Equations

arXiv - Machine Learning · 4 min ·
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