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Machine Learning

[D] ICML Rebuttal Question

I am currently working on my response on the rebuttal acknowledgments for ICML and I doubting how to handle the strawman argument of that...

Reddit - Machine Learning · 1 min ·
Machine Learning

[D] ML researcher looking to switch to a product company.

Hey, I am an AI researcher currently working in a deep tech company as a data scientist. Prior to this, I was doing my PhD. My current ro...

Reddit - Machine Learning · 1 min ·
Machine Learning

Building behavioural response models of public figures using Brain scan data (Predict their next move using psychological modelling) [P]

Hey guys, I’m the same creator of Netryx V2, the geolocation tool. I’ve been working on something new called COGNEX. It learns how a pers...

Reddit - Machine Learning · 1 min ·

All Content

[2504.16956] GeneMamba: An Efficient and Effective Foundation Model on Single Cell Data
Llms

[2504.16956] GeneMamba: An Efficient and Effective Foundation Model on Single Cell Data

Abstract page for arXiv paper 2504.16956: GeneMamba: An Efficient and Effective Foundation Model on Single Cell Data

arXiv - Machine Learning · 4 min ·
[2503.14553] Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels to Embeddings for Task-Specific Data Distributions
Machine Learning

[2503.14553] Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels to Embeddings for Task-Specific Data Distributions

Abstract page for arXiv paper 2503.14553: Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels ...

arXiv - Machine Learning · 4 min ·
[2507.12602] MS-DGCNN++: Multi-Scale Dynamic Graph Convolution with Scale-Dependent Normalization for Robust LiDAR Tree Species Classification
Machine Learning

[2507.12602] MS-DGCNN++: Multi-Scale Dynamic Graph Convolution with Scale-Dependent Normalization for Robust LiDAR Tree Species Classification

Abstract page for arXiv paper 2507.12602: MS-DGCNN++: Multi-Scale Dynamic Graph Convolution with Scale-Dependent Normalization for Robust...

arXiv - AI · 4 min ·
[2502.10001] EmbBERT: Attention Under 2 MB Memory
Machine Learning

[2502.10001] EmbBERT: Attention Under 2 MB Memory

Abstract page for arXiv paper 2502.10001: EmbBERT: Attention Under 2 MB Memory

arXiv - Machine Learning · 4 min ·
[2412.08686] LatentQA: Teaching LLMs to Decode Activations Into Natural Language
Llms

[2412.08686] LatentQA: Teaching LLMs to Decode Activations Into Natural Language

Abstract page for arXiv paper 2412.08686: LatentQA: Teaching LLMs to Decode Activations Into Natural Language

arXiv - Machine Learning · 4 min ·
[2411.00623] Replay-Free Continual Low-Rank Adaptation with Dynamic Memory
Machine Learning

[2411.00623] Replay-Free Continual Low-Rank Adaptation with Dynamic Memory

Abstract page for arXiv paper 2411.00623: Replay-Free Continual Low-Rank Adaptation with Dynamic Memory

arXiv - Machine Learning · 4 min ·
[2506.01929] Image Generation from Contextually-Contradictory Prompts
Machine Learning

[2506.01929] Image Generation from Contextually-Contradictory Prompts

Abstract page for arXiv paper 2506.01929: Image Generation from Contextually-Contradictory Prompts

arXiv - AI · 4 min ·
[2410.12164] Table-LLM-Specialist: Language Model Specialists for Tables using Iterative Generator-Validator Fine-tuning
Llms

[2410.12164] Table-LLM-Specialist: Language Model Specialists for Tables using Iterative Generator-Validator Fine-tuning

Abstract page for arXiv paper 2410.12164: Table-LLM-Specialist: Language Model Specialists for Tables using Iterative Generator-Validator...

arXiv - Machine Learning · 4 min ·
[2407.00644] Clusterpath Gaussian Graphical Modeling
Machine Learning

[2407.00644] Clusterpath Gaussian Graphical Modeling

Abstract page for arXiv paper 2407.00644: Clusterpath Gaussian Graphical Modeling

arXiv - Machine Learning · 4 min ·
[2403.16125] Arena: Efficiently Training Large Models via Dynamic Scheduling and Adaptive Parallelism Co-Design
Machine Learning

[2403.16125] Arena: Efficiently Training Large Models via Dynamic Scheduling and Adaptive Parallelism Co-Design

Abstract page for arXiv paper 2403.16125: Arena: Efficiently Training Large Models via Dynamic Scheduling and Adaptive Parallelism Co-Design

arXiv - Machine Learning · 4 min ·
[2504.07396] Automating quantum feature map design via large language models
Llms

[2504.07396] Automating quantum feature map design via large language models

Abstract page for arXiv paper 2504.07396: Automating quantum feature map design via large language models

arXiv - AI · 4 min ·
[2312.10618] Sparse Learning and Class Probability Estimation with Weighted Support Vector Machines
Machine Learning

[2312.10618] Sparse Learning and Class Probability Estimation with Weighted Support Vector Machines

Abstract page for arXiv paper 2312.10618: Sparse Learning and Class Probability Estimation with Weighted Support Vector Machines

arXiv - Machine Learning · 4 min ·
[2309.07250] All you need is spin: SU(2) equivariant variational quantum circuits based on spin networks
Machine Learning

[2309.07250] All you need is spin: SU(2) equivariant variational quantum circuits based on spin networks

Abstract page for arXiv paper 2309.07250: All you need is spin: SU(2) equivariant variational quantum circuits based on spin networks

arXiv - Machine Learning · 4 min ·
[2503.04945] Collaborative Evaluation of Deepfake Text with Deliberation-Enhancing Dialogue Systems
Machine Learning

[2503.04945] Collaborative Evaluation of Deepfake Text with Deliberation-Enhancing Dialogue Systems

Abstract page for arXiv paper 2503.04945: Collaborative Evaluation of Deepfake Text with Deliberation-Enhancing Dialogue Systems

arXiv - AI · 4 min ·
[2503.04406] Training-free Adjustable Polynomial Graph Filtering for Ultra-fast Multimodal Recommendation
Machine Learning

[2503.04406] Training-free Adjustable Polynomial Graph Filtering for Ultra-fast Multimodal Recommendation

Abstract page for arXiv paper 2503.04406: Training-free Adjustable Polynomial Graph Filtering for Ultra-fast Multimodal Recommendation

arXiv - AI · 4 min ·
[2306.14853] Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles
Machine Learning

[2306.14853] Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles

Abstract page for arXiv paper 2306.14853: Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles

arXiv - Machine Learning · 4 min ·
[2502.01969] Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration
Llms

[2502.01969] Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration

Abstract page for arXiv paper 2502.01969: Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration

arXiv - AI · 4 min ·
[2202.05775] Inference of Multiscale Gaussian Graphical Model
Machine Learning

[2202.05775] Inference of Multiscale Gaussian Graphical Model

Abstract page for arXiv paper 2202.05775: Inference of Multiscale Gaussian Graphical Model

arXiv - Machine Learning · 4 min ·
[2306.05036] Mapping the Challenges of HCI: An Application and Evaluation of ChatGPT for Mining Insights at Scale
Llms

[2306.05036] Mapping the Challenges of HCI: An Application and Evaluation of ChatGPT for Mining Insights at Scale

Abstract page for arXiv paper 2306.05036: Mapping the Challenges of HCI: An Application and Evaluation of ChatGPT for Mining Insights at ...

arXiv - AI · 4 min ·
[2603.17112] Cascade-Aware Multi-Agent Routing: Spatio-Temporal Sidecars and Geometry-Switching
Machine Learning

[2603.17112] Cascade-Aware Multi-Agent Routing: Spatio-Temporal Sidecars and Geometry-Switching

Abstract page for arXiv paper 2603.17112: Cascade-Aware Multi-Agent Routing: Spatio-Temporal Sidecars and Geometry-Switching

arXiv - AI · 4 min ·
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