Machine Learning

Authors and titles for cs.LG in Feb 2024, skipping first 50

[51]  arXiv:2402.00607 [pdf, other]

Title: Are Synthetic Time-series Data Really not as Good as Real Data?

Authors: Fanzhe Fu, Junru Chen, Jing Zhang, Carl Yang, Lvbin Ma, Yang Yang

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

[52]  arXiv:2402.00608 [pdf, other]

Title: Deep Clustering Using the Soft Silhouette Score: Towards Compact and Well-Separated Clusters

Authors: Georgios Vardakas, Ioannis Papakostas, Aristidis Likas

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

[53]  arXiv:2402.00638 [pdf, ps, other]

Title: Random Forest-Based Prediction of Stroke Outcome

Authors: Carlos Fernandez-Lozano, Pablo Hervella, Virginia Mato-Abad, Manuel Rodriguez-Yanez, Sonia Suarez-Garaboa, Iria Lopez-Dequidt, Ana Estany-Gestal, Tomas Sobrino, Francisco Campos, Jose Castillo, Santiago Rodriguez-Yanez, Ramon Iglesias-Rey

Comments: 12 pages, 5 figures

Subjects: Machine Learning (cs.LG)

[54]  arXiv:2402.00654 [pdf, ps, other]

Title: Improving the accuracy of freight mode choice models: A case study using the 2017 CFS PUF data set and ensemble learning techniques

Authors: Diyi Liu, Hyeonsup Lim, Majbah Uddin, Yuandong Liu, Lee D. Han, Ho-ling Hwang, Shih-Miao Chin

Journal-ref: Expert Systems with Applications, 240, 122478 (2024)

Subjects: Machine Learning (cs.LG)

[55]  arXiv:2402.00659 [pdf, ps, other]

Title: Modeling Freight Mode Choice Using Machine Learning Classifiers: A Comparative Study Using the Commodity Flow Survey (CFS) Data

Authors: Majbah Uddin, Sabreena Anowar, Naveen Eluru

Journal-ref: Transportation Planning and Technology, 44(5), 543-559 (2021)

Subjects: Machine Learning (cs.LG)

[56]  arXiv:2402.00705 [pdf, ps, other]

Title: Combining the Strengths of Dutch Survey and Register Data in a Data Challenge to Predict Fertility (PreFer)

Authors: Elizaveta Sivak, Paulina Pankowska, Adrienne Mendrik, Tom Emery, Javier Garcia-Bernardo, Seyit Hocuk, Kasia Karpinska, Angelica Maineri, Joris Mulder, Malvina Nissim, Gert Stulp

Subjects: Machine Learning (cs.LG); Databases (cs.DB)

[57]  arXiv:2402.00711 [pdf, other]

Title: Explaining Text Classifiers with Counterfactual Representations

Authors: Pirmin Lemberger, Antoine Saillenfest

Comments: 24 pages, 4 figures

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

[58]  arXiv:2402.00728 [pdf, other]

Title: Dropout-Based Rashomon Set Exploration for Efficient Predictive Multiplicity Estimation

Authors: Hsiang Hsu, Guihong Li, Shaohan Hu, Chun-Fu (Richard) Chen

Comments: ICLR 2024

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

[59]  arXiv:2402.00732 [pdf, other]

Title: MobilityDL: A Review of Deep Learning From Trajectory Data

Authors: Anita Graser, Anahid Jalali, Jasmin Lampert, Axel Weißenfeld, Krzysztof Janowicz

Comments: Submitted to Geoinformatica

Subjects: Machine Learning (cs.LG)

[60]  arXiv:2402.00743 [pdf, other]

Title: Benefits of Transformer: In-Context Learning in Linear Regression Tasks with Unstructured Data

Authors: Yue Xing, Xiaofeng Lin, Namjoon Suh, Qifan Song, Guang Cheng

Subjects: Machine Learning (cs.LG); Computation and Language (cs.CL); Machine Learning (stat.ML)

[61]  arXiv:2402.00751 [pdf, other]

Title: Unlearnable Algorithms for In-context Learning

Authors: Andrei Muresanu, Anvith Thudi, Michael R. Zhang, Nicolas Papernot

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

[62]  arXiv:2402.00759 [pdf, other]

Title: Building Expressive and Tractable Probabilistic Generative Models: A Review

Authors: Sahil Sidheekh, Sriraam Natarajan

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

[63]  arXiv:2402.00761 [pdf, ps, other]

Title: Control-Theoretic Techniques for Online Adaptation of Deep Neural Networks in Dynamical Systems

Authors: Jacob G. Elkins, Farbod Fahimi

Comments: Preprint version

Subjects: Machine Learning (cs.LG); Neural and Evolutionary Computing (cs.NE); Robotics (cs.RO); Systems and Control (eess.SY)

[64]  arXiv:2402.00782 [pdf, other]

Title: Dense Reward for Free in Reinforcement Learning from Human Feedback

Authors: Alex J. Chan, Hao Sun, Samuel Holt, Mihaela van der Schaar

Subjects: Machine Learning (cs.LG)

[65]  arXiv:2402.00789 [pdf, other]

Title: Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces

Authors: Chloe Wang, Oleksii Tsepa, Jun Ma, Bo Wang

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

[66]  arXiv:2402.00793 [pdf, other]

Title: Human Expertise in Algorithmic Prediction

Authors: Rohan Alur, Manish Raghavan, Devavrat Shah

Comments: 35 pages, 13 figures

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

[67]  arXiv:2402.00795 [pdf, other]

Title: LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law

Authors: Toni J.B. Liu, Nicolas Boullé, Raphaël Sarfati, Christopher J. Earls

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

[68]  arXiv:2402.00798 [pdf, other]

Title: Formal-LLM: Integrating Formal Language and Natural Language for Controllable LLM-based Agents

Authors: Zelong Li, Wenyue Hua, Hao Wang, He Zhu, Yongfeng Zhang

Comments: 21 pages, 6 figures; comments and suggestions are welcome

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Formal Languages and Automata Theory (cs.FL)

[69]  arXiv:2402.00803 [pdf, other]

Title: Signal Quality Auditing for Time-series Data

Authors: Chufan Gao, Nicholas Gisolfi, Artur Dubrawski

Subjects: Machine Learning (cs.LG); Signal Processing (eess.SP)

[70]  arXiv:2402.00807 [pdf, other]

Title: Distilling Conditional Diffusion Models for Offline Reinforcement Learning through Trajectory Stitching

Authors: Shangzhe Li, Xinhua Zhang

Subjects: Machine Learning (cs.LG)

[71]  arXiv:2402.00809 [pdf, other]

Title: Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI

Authors: Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang

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

[72]  arXiv:2402.00816 [pdf, other]

Title: Leveraging Approximate Model-based Shielding for Probabilistic Safety Guarantees in Continuous Environments

Authors: Alexander W. Goodall, Francesco Belardinelli

Comments: Accepted as an Extended Abstract at AAMAS 2024

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

[73]  arXiv:2402.00823 [pdf, other]

Title: SLIM: Skill Learning with Multiple Critics

Authors: David Emukpere, Bingbing Wu, Julien Perez, Jean-Michel Renders

Comments: Accepted at IEEE ICRA 2024

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

[74]  arXiv:2402.00849 [pdf, other]

Title: Score-based Causal Representation Learning: Linear and General Transformations

Authors: Burak Varıcı, Emre Acartürk, Karthikeyan Shanmugam, Abhishek Kumar, Ali Tajer

Comments: (updated literature review) Linear transformations: stronger results than our previous paper Score-based Causal Representation Learning with Interventions (arXiv:2301.08230). General transformations: results also appear in our paper General Identifiability and Achievability for Causal Representation Learning (arXiv:2310.15450) accepted to AISTATS 2024 (oral). arXiv admin note: text overlap with arXiv:2310.15450

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

[75]  arXiv:2402.00851 [pdf, other]

Title: Data Augmentation Scheme for Raman Spectra with Highly Correlated Annotations

Authors: Christoph Lange, Isabel Thiele, Lara Santolin, Sebastian L. Riedel, Maxim Borisyak, Peter Neubauer, M. Nicolas Cruz Bournazou

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