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Machine Learning

[R], 31 MILLIONS High frequency data, Light GBM worked perfectly

We just published a paper on predicting adverse selection in high-frequency crypto markets using LightGBM, and I wanted to share it here ...

Reddit - Machine Learning · 1 min ·
Machine Learning

[D] Those of you with 10+ years in ML — what is the public completely wrong about?

For those of you who've been in ML/AI research or applied ML for 10+ years — what's the gap between what the public thinks AI is doing vs...

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 ·

All Content

[2510.14814] Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift
Machine Learning

[2510.14814] Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift

Abstract page for arXiv paper 2510.14814: Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift

arXiv - Machine Learning · 4 min ·
[2510.15495] OffSim: Offline Simulator for Model-based Offline Inverse Reinforcement Learning
Machine Learning

[2510.15495] OffSim: Offline Simulator for Model-based Offline Inverse Reinforcement Learning

Abstract page for arXiv paper 2510.15495: OffSim: Offline Simulator for Model-based Offline Inverse Reinforcement Learning

arXiv - Machine Learning · 4 min ·
[2510.14751] Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries
Llms

[2510.14751] Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries

Abstract page for arXiv paper 2510.14751: Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries

arXiv - Machine Learning · 3 min ·
[2510.06020] RamPINN: Recovering Raman Spectra From Coherent Anti-Stokes Spectra Using Embedded Physics
Machine Learning

[2510.06020] RamPINN: Recovering Raman Spectra From Coherent Anti-Stokes Spectra Using Embedded Physics

Abstract page for arXiv paper 2510.06020: RamPINN: Recovering Raman Spectra From Coherent Anti-Stokes Spectra Using Embedded Physics

arXiv - Machine Learning · 4 min ·
[2510.00430] PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment
Machine Learning

[2510.00430] PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment

Abstract page for arXiv paper 2510.00430: PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment

arXiv - Machine Learning · 4 min ·
[2510.01169] Fiaingen: A financial time series generative method matching real-world data quality
Machine Learning

[2510.01169] Fiaingen: A financial time series generative method matching real-world data quality

Abstract page for arXiv paper 2510.01169: Fiaingen: A financial time series generative method matching real-world data quality

arXiv - Machine Learning · 4 min ·
[2509.24140] A signal separation view of classification
Machine Learning

[2509.24140] A signal separation view of classification

Abstract page for arXiv paper 2509.24140: A signal separation view of classification

arXiv - Machine Learning · 3 min ·
[2508.17381] DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning
Machine Learning

[2508.17381] DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning

Abstract page for arXiv paper 2508.17381: DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning

arXiv - Machine Learning · 3 min ·
[2508.02330] A Compression Based Classification Framework Using Symbolic Dynamics of Chaotic Maps
Machine Learning

[2508.02330] A Compression Based Classification Framework Using Symbolic Dynamics of Chaotic Maps

Abstract page for arXiv paper 2508.02330: A Compression Based Classification Framework Using Symbolic Dynamics of Chaotic Maps

arXiv - Machine Learning · 4 min ·
[2507.21037] When Brain Foundation Model Meets Cauchy-Schwarz Divergence: A New Framework for Cross-Subject Motor Imagery Decoding
Llms

[2507.21037] When Brain Foundation Model Meets Cauchy-Schwarz Divergence: A New Framework for Cross-Subject Motor Imagery Decoding

Abstract page for arXiv paper 2507.21037: When Brain Foundation Model Meets Cauchy-Schwarz Divergence: A New Framework for Cross-Subject ...

arXiv - Machine Learning · 4 min ·
[2507.07580] COALA: Numerically Stable and Efficient Framework for Context-Aware Low-Rank Approximation
Machine Learning

[2507.07580] COALA: Numerically Stable and Efficient Framework for Context-Aware Low-Rank Approximation

Abstract page for arXiv paper 2507.07580: COALA: Numerically Stable and Efficient Framework for Context-Aware Low-Rank Approximation

arXiv - Machine Learning · 4 min ·
[2506.06482] TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness
Machine Learning

[2506.06482] TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness

Abstract page for arXiv paper 2506.06482: TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness

arXiv - Machine Learning · 4 min ·
[2506.06303] Reward Is Enough: LLMs Are In-Context Reinforcement Learners
Llms

[2506.06303] Reward Is Enough: LLMs Are In-Context Reinforcement Learners

Abstract page for arXiv paper 2506.06303: Reward Is Enough: LLMs Are In-Context Reinforcement Learners

arXiv - Machine Learning · 4 min ·
[2506.04831] EHR2Path: Scalable Modeling of Longitudinal Patient Pathways from Multimodal Electronic Health Records
Machine Learning

[2506.04831] EHR2Path: Scalable Modeling of Longitudinal Patient Pathways from Multimodal Electronic Health Records

Abstract page for arXiv paper 2506.04831: EHR2Path: Scalable Modeling of Longitudinal Patient Pathways from Multimodal Electronic Health ...

arXiv - Machine Learning · 4 min ·
[2505.22785] Navigating the Latent Space Dynamics of Neural Models
Machine Learning

[2505.22785] Navigating the Latent Space Dynamics of Neural Models

Abstract page for arXiv paper 2505.22785: Navigating the Latent Space Dynamics of Neural Models

arXiv - Machine Learning · 4 min ·
[2505.16950] Bottlenecked Transformers: Periodic KV Cache Consolidation for Generalised Reasoning
Llms

[2505.16950] Bottlenecked Transformers: Periodic KV Cache Consolidation for Generalised Reasoning

Abstract page for arXiv paper 2505.16950: Bottlenecked Transformers: Periodic KV Cache Consolidation for Generalised Reasoning

arXiv - Machine Learning · 4 min ·
[2505.15516] Explainable embeddings with Distance Explainer
Machine Learning

[2505.15516] Explainable embeddings with Distance Explainer

Abstract page for arXiv paper 2505.15516: Explainable embeddings with Distance Explainer

arXiv - Machine Learning · 4 min ·
[2502.01521] Symmetry-Guided Memory Augmentation for Efficient Locomotion Learning
Machine Learning

[2502.01521] Symmetry-Guided Memory Augmentation for Efficient Locomotion Learning

Abstract page for arXiv paper 2502.01521: Symmetry-Guided Memory Augmentation for Efficient Locomotion Learning

arXiv - Machine Learning · 3 min ·
[2409.11847] An efficient wavelet-based physics-informed neural network for multiscale problems
Machine Learning

[2409.11847] An efficient wavelet-based physics-informed neural network for multiscale problems

Abstract page for arXiv paper 2409.11847: An efficient wavelet-based physics-informed neural network for multiscale problems

arXiv - Machine Learning · 4 min ·
[2406.01969] Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training
Machine Learning

[2406.01969] Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training

Abstract page for arXiv paper 2406.01969: Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training

arXiv - Machine Learning · 4 min ·
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