Machine Learning

Authors and titles for cs.LG in Aug 2023

[1]  arXiv:2308.00031 [pdf, other]

Title: Reinforcement Learning for Generative AI: State of the Art, Opportunities and Open Research Challenges

Authors: Giorgio Franceschelli, Mirco Musolesi

Comments: Published in JAIR at this https URL

Journal-ref: JAIR 79 (2024) 417-446

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI)

[2]  arXiv:2308.00074 [pdf, ps, other]

Title: Using Kernel SHAP XAI Method to optimize the Network Anomaly Detection Model

Authors: Khushnaseeb Roshan, Aasim Zafar

Comments: 7 Pages, 8 Figures, 3 Tables

Subjects: Machine Learning (cs.LG); Cryptography and Security (cs.CR)

[3]  arXiv:2308.00086 [pdf, other]

Title: An unsupervised machine-learning-based shock sensor for high-order supersonic flow solvers

Authors: Andrés Mateo-Gabín, Kenza Tlales, Eusebio Valero, Esteban Ferrer, Gonzalo Rubio

Subjects: Machine Learning (cs.LG); Computational Physics (physics.comp-ph); Fluid Dynamics (physics.flu-dyn)

[4]  arXiv:2308.00089 [pdf, ps, other]

Title: New Lower Bounds for Testing Monotonicity and Log Concavity of Distributions

Authors: Yuqian Cheng, Daniel M. Kane, Zhicheng Zheng

Subjects: Machine Learning (cs.LG); Statistics Theory (math.ST)

[5]  arXiv:2308.00127 [pdf, other]

Title: DiviML: A Module-based Heuristic for Mapping Neural Networks onto Heterogeneous Platforms

Authors: Yassine Ghannane, Mohamed S. Abdelfattah

Comments: accepted at ICCAD'23

Subjects: Machine Learning (cs.LG); Distributed, Parallel, and Cluster Computing (cs.DC); Software Engineering (cs.SE)

[6]  arXiv:2308.00133 [pdf, other]

Title: A Suite of Fairness Datasets for Tabular Classification

Authors: Martin Hirzel, Michael Feffer

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Computers and Society (cs.CY)

[7]  arXiv:2308.00142 [pdf, other]

Title: Semi-Supervised Laplacian Learning on Stiefel Manifolds

Authors: Chester Holtz, Pengwen Chen, Alexander Cloninger, Chung-Kuan Cheng, Gal Mishne

Subjects: Machine Learning (cs.LG)

[8]  arXiv:2308.00146 [pdf, other]

Title: DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification

Authors: Sandra Gilhuber, Julian Busch, Daniel Rotthues, Christian M. M. Frey, Thomas Seidl

Comments: Accepted @ ECML PKDD 2023. This is the author's version of the work. The definitive Version of Record will be published in the Proceedings of ECML PKDD 2023

Journal-ref: ECML PKDD 2023: Machine Learning and Knowledge Discovery in Databases: Research Track pp 75-91

Subjects: Machine Learning (cs.LG); Social and Information Networks (cs.SI)

[9]  arXiv:2308.00176 [pdf, other]

Title: A Flow Artist for High-Dimensional Cellular Data

Authors: Kincaid MacDonald, Dhananjay Bhaskar, Guy Thampakkul, Nhi Nguyen, Joia Zhang, Michael Perlmutter, Ian Adelstein, Smita Krishnaswamy

Comments: Accepted for publication in 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP)

Subjects: Machine Learning (cs.LG); Quantitative Methods (q-bio.QM)

[10]  arXiv:2308.00177 [pdf, other]

Title: Pretrained deep models outperform GBDTs in Learning-To-Rank under label scarcity

Authors: Charlie Hou, Kiran Koshy Thekumparampil, Michael Shavlovsky, Giulia Fanti, Yesh Dattatreya, Sujay Sanghavi

Comments: ICML-MFPL 2023 Workshop Oral

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI)

[11]  arXiv:2308.00189 [pdf, other]

Title: Generative Models as a Complex Systems Science: How can we make sense of large language model behavior?

Authors: Ari Holtzman, Peter West, Luke Zettlemoyer

Comments: 15 pages, 7 figures

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Computation and Language (cs.CL)

[12]  arXiv:2308.00231 [pdf, other]

Title: Capsa: A Unified Framework for Quantifying Risk in Deep Neural Networks

Authors: Sadhana Lolla, Iaroslav Elistratov, Alejandro Perez, Elaheh Ahmadi, Daniela Rus, Alexander Amini

Comments: Neural Information Processing Systems (NeurIPS) 2022. Workshop on Machine Learning for Autonomous Driving (ML4AD)

Journal-ref: Neural Information Processing Systems (NeurIPS) 2022. Workshop on Machine Learning for Autonomous Driving (ML4AD)

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI)

[13]  arXiv:2308.00246 [pdf, other]

Title: EEG-based Cognitive Load Classification using Feature Masked Autoencoding and Emotion Transfer Learning

Authors: Dustin Pulver, Prithila Angkan, Paul Hungler, Ali Etemad

Comments: This paper has been accepted to the 25th International Conference on Multimodal Interaction (ICMI 2023). 8 pages, 6 figures, 6 tables

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC)

[14]  arXiv:2308.00258 [pdf, other]

Title: AQUILA: Communication Efficient Federated Learning with Adaptive Quantization in Device Selection Strategy

Authors: Zihao Zhao, Yuzhu Mao, Zhenpeng Shi, Yang Liu, Tian Lan, Wenbo Ding, Xiao-Ping Zhang

Subjects: Machine Learning (cs.LG); Distributed, Parallel, and Cluster Computing (cs.DC)

[15]  arXiv:2308.00263 [pdf, other]

Title: Asynchronous Federated Learning with Bidirectional Quantized Communications and Buffered Aggregation

Authors: Tomas Ortega, Hamid Jafarkhani

Comments: Accepted at the 2023 ICML Workshop of Federated Learning and Analytics in Practice

Subjects: Machine Learning (cs.LG); Signal Processing (eess.SP); Optimization and Control (math.OC)

[16]  arXiv:2308.00273 [pdf, other]

Title: Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions

Authors: Samantha Chen, Yusu Wang

Comments: Accepted to NeurIPS 2023

Subjects: Machine Learning (cs.LG)

[17]  arXiv:2308.00278 [pdf, other]

Title: Classes are not Clusters: Improving Label-based Evaluation of Dimensionality Reduction

Authors: Hyeon Jeon, Yun-Hsin Kuo, Michaël Aupetit, Kwan-Liu Ma, Jinwook Seo

Comments: IEEE Transactions on Visualization and Computer Graphics (TVCG) (Proc. IEEE VIS 2023)

Subjects: Machine Learning (cs.LG)

[18]  arXiv:2308.00279 [pdf, other]

Title: Robust Positive-Unlabeled Learning via Noise Negative Sample Self-correction

Authors: Zhangchi Zhu, Lu Wang, Pu Zhao, Chao Du, Wei Zhang, Hang Dong, Bo Qiao, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang

Comments: Accepted at KDD2023

Subjects: Machine Learning (cs.LG); Computer Vision and Pattern Recognition (cs.CV)

[19]  arXiv:2308.00280 [pdf, other]

Title: Data Collaboration Analysis applied to Compound Datasets and the Introduction of Projection data to Non-IID settings

Authors: Akihiro Mizoguchi, Anna Bogdanova, Akira Imakura, Tetsuya Sakurai

Subjects: Machine Learning (cs.LG)

[20]  arXiv:2308.00282 [pdf, other]

Title: ZADU: A Python Library for Evaluating the Reliability of Dimensionality Reduction Embeddings

Authors: Hyeon Jeon, Aeri Cho, Jinhwa Jang, Soohyun Lee, Jake Hyun, Hyung-Kwon Ko, Jaemin Jo, Jinwook Seo

Comments: 2023 IEEE Visualization and Visual Analytics (IEEE VIS 2023) Short paper

Subjects: Machine Learning (cs.LG)

[21]  arXiv:2308.00285 [pdf, other]

Title: Predictive Modeling through Hyper-Bayesian Optimization

Authors: Manisha Senadeera, Santu Rana, Sunil Gupta, Svetha Venkatesh

Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML)

[22]  arXiv:2308.00311 [pdf, other]

Title: Doubly Robust Instance-Reweighted Adversarial Training

Authors: Daouda Sow, Sen Lin, Zhangyang Wang, Yingbin Liang

Comments: Submitted for publication

Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML)

[23]  arXiv:2308.00318 [pdf, other]

Title: Pixel to policy: DQN Encoders for within & cross-game reinforcement learning

Authors: Ashrya Agrawal, Priyanshi Shah, Sourabh Prakash

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Robotics (cs.RO)

[24]  arXiv:2308.00346 [pdf, other]

Title: Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness

Authors: Ruoxi Qin, Linyuan Wang, Xuehui Du, Xingyuan Chen, Bin Yan

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR)

[25]  arXiv:2308.00350 [pdf, ps, other]

Title: Learning Green's Function Efficiently Using Low-Rank Approximations

Authors: Kishan Wimalawarne, Taiji Suzuki, Sophie Langer

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Numerical Analysis (math.NA)