Trans. Mach. Learn. Res.

Keyphrases

Publications

volume 2023, 2023

Christoffer Löffler, Kion Fallah, Stefano Fenu, Dario Zanca, Björn M. Eskofier, Christopher John Rozell, Christopher Mutschler
Active Learning of Ordinal Embeddings: A User Study on Football Data. Trans. Mach. Learn. Res. 2023 (2023)
Zhangheng Li, Tianlong Chen, Linyi Li, Bo Li, Zhangyang Wang
Can Pruning Improve Certified Robustness of Neural Networks? Trans. Mach. Learn. Res. 2023 (2023)
Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu
Continual Learning by Modeling Intra-Class Variation. Trans. Mach. Learn. Res. 2023 (2023)
Oyku Deniz Kose, Yanning Shen
Fast&Fair: Training Acceleration and Bias Mitigation for GNNs. Trans. Mach. Learn. Res. 2023 (2023)
Kiri L. Wagstaff, Thomas G. Dietterich
Hidden Heterogeneity: When to Choose Similarity-Based Calibration. Trans. Mach. Learn. Res. 2023 (2023)
Sami Jullien, Mozhdeh Ariannezhad, Paul Groth, Maarten de Rijke
A Simulation Environment and Reinforcement Learning Method for Waste Reduction. Trans. Mach. Learn. Res. 2023 (2023)
Zhen Xu, Quanming Yao, Yong Li, Qiang Yang
Understanding and Simplifying Architecture Search in Spatio-Temporal Graph Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
David Chiang, Alexander M. Rush, Boaz Barak
Named Tensor Notation. Trans. Mach. Learn. Res. 2023 (2023)
Rahul Singh, Yongxin Chen
Signed Graph Neural Networks: A Frequency Perspective. Trans. Mach. Learn. Res. 2023 (2023)
Heiko Zimmermann, Fredrik Lindsten, Jan-Willem van de Meent, Christian A. Naesseth
A Variational Perspective on Generative Flow Networks. Trans. Mach. Learn. Res. 2023 (2023)
Mikko A. Heikkilä, Matthew Ashman, Siddharth Swaroop, Richard E. Turner, Antti Honkela
Differentially private partitioned variational inference. Trans. Mach. Learn. Res. 2023 (2023)
Simon Hubbert, Emilio Porcu, Chris J. Oates, Mark Girolami
Sobolev Spaces, Kernels and Discrepancies over Hyperspheres. Trans. Mach. Learn. Res. 2023 (2023)
Fabian Schaipp, Robert M. Gower, Michael Ulbrich
A Stochastic Proximal Polyak Step Size. Trans. Mach. Learn. Res. 2023 (2023)
Soufiane Hayou
On the infinite-depth limit of finite-width neural networks. Trans. Mach. Learn. Res. 2023 (2023)
Zhiliang Peng, Li Dong, Hangbo Bao, Furu Wei, Qixiang Ye
A Unified View of Masked Image Modeling. Trans. Mach. Learn. Res. 2023 (2023)
Sander Dalm, Nasir Ahmad, Luca Ambrogioni, Marcel van Gerven
Gradient-adjusted Incremental Target Propagation Provides Effective Credit Assignment in Deep Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
Axel Böhm
Solving Nonconvex-Nonconcave Min-Max Problems exhibiting Weak Minty Solutions. Trans. Mach. Learn. Res. 2023 (2023)
Valerii Likhosherstov, Anurag Arnab, Krzysztof Marcin Choromanski, Mario Lucic, Yi Tay, Mostafa Dehghani
PolyViT: Co-training Vision Transformers on Images, Videos and Audio. Trans. Mach. Learn. Res. 2023 (2023)
Chacha Chen, Shi Feng, Amit Sharma, Chenhao Tan
Machine Explanations and Human Understanding. Trans. Mach. Learn. Res. 2023 (2023)
Ondrej Such, René Fabricius
Bridging performance gap between minimal and maximal SVM models. Trans. Mach. Learn. Res. 2023 (2023)
Dennis Ulmer, Christian Hardmeier, Jes Frellsen
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation. Trans. Mach. Learn. Res. 2023 (2023)
Patrick M. Soga, David Chiang
Bridging Graph Position Encodings for Transformers with Weighted Graph-Walking Automata. Trans. Mach. Learn. Res. 2023 (2023)
Maximilian Stubbemann, Tom Hanika, Friedrich Martin Schneider
Intrinsic Dimension for Large-Scale Geometric Learning. Trans. Mach. Learn. Res. 2023 (2023)
Saiteja Utpala, Praneeth Vepakomma, Nina Miolane
Differentially Private Fréchet Mean on the Manifold of Symmetric Positive Definite (SPD) Matrices with log-Euclidean Metric. Trans. Mach. Learn. Res. 2023 (2023)
Matthew James Vowels, Sina Akbari, Necati Cihan Camgöz, Richard Bowden
A Free Lunch with Influence Functions? An Empirical Evaluation of Influence Functions for Average Treatment Effect Estimation. Trans. Mach. Learn. Res. 2023 (2023)
Zheng Shi, Abdurakhmon Sadiev, Nicolas Loizou, Peter Richtárik, Martin Takác
AI-SARAH: Adaptive and Implicit Stochastic Recursive Gradient Methods. Trans. Mach. Learn. Res. 2023 (2023)
Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio
DEUP: Direct Epistemic Uncertainty Prediction. Trans. Mach. Learn. Res. 2023 (2023)
Diego A. Velázquez, Pau Rodríguez, Alexandre Lacoste, Issam H. Laradji, F. Xavier Roca, Jordi Gonzàlez
Explaining Visual Counterfactual Explainers. Trans. Mach. Learn. Res. 2023 (2023)
Mihaela Rosca, Yan Wu, Chongli Qin, Benoit Dherin
On a continuous time model of gradient descent dynamics and instability in deep learning. Trans. Mach. Learn. Res. 2023 (2023)
Rishi Sonthalia, Raj Rao Nadakuditi
Training Data Size Induced Double Descent For Denoising Feedforward Neural Networks and the Role of Training Noise. Trans. Mach. Learn. Res. 2023 (2023)
Guillaume Morel, Lucas Drumetz, Simon Benaïchouche, Nicolas Courty, François Rousseau
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows. Trans. Mach. Learn. Res. 2023 (2023)
Franz M. Rohrhofer, Stefan Posch, Clemens Gößnitzer, Bernhard C. Geiger
On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
Matteo Zecchin, Marios Kountouris, David Gesbert
Communication-Efficient Distributionally Robust Decentralized Learning. Trans. Mach. Learn. Res. 2023 (2023)
Harsh Satija, Alessandro Lazaric, Matteo Pirotta, Joelle Pineau
Group Fairness in Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023)
Frederik Harder, Milad Jalali, Danica J. Sutherland, Mijung Park
Pre-trained Perceptual Features Improve Differentially Private Image Generation. Trans. Mach. Learn. Res. 2023 (2023)
Angus Galloway, Anna Golubeva, Mahmoud Salem, Mihai Nica, Yani A. Ioannou, Graham W. Taylor
Bounding generalization error with input compression: An empirical study with infinite-width networks. Trans. Mach. Learn. Res. 2023 (2023)
Mohamed Abdelhack, Jiaming Zhang, Sandhya Tripathi, Bradley A. Fritz, Daniel Felsky, Michael Avidan, Yi-Xin Chen, Christopher Ryan King
A Modulation Layer to Increase Neural Network Robustness Against Data Quality Issues. Trans. Mach. Learn. Res. 2023 (2023)
Jing Wu, David Pichler, Daniel Marley, Naira Hovakimyan, David Wilson, Jennifer A. Hobbs
Extended Agriculture-Vision: An Extension of a Large Aerial Image Dataset for Agricultural Pattern Analysis. Trans. Mach. Learn. Res. 2023 (2023)
Vikranth Dwaracherla, Zheng Wen, Ian Osband, Xiuyuan Lu, Seyed Mohammad Asghari, Benjamin Van Roy
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping. Trans. Mach. Learn. Res. 2023 (2023)
Tony Tohme, Dehong Liu, Kamal Youcef-Toumi
GSR: A Generalized Symbolic Regression Approach. Trans. Mach. Learn. Res. 2023 (2023)
Diyuan Wu, Vyacheslav Kungurtsev, Marco Mondelli
Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence. Trans. Mach. Learn. Res. 2023 (2023)
Felipe A. Tobar, Elsa Cazelles, Taco de Wolff
Computationally-efficient initialisation of GPs: The generalised variogram method. Trans. Mach. Learn. Res. 2023 (2023)
Jicong Fan, Lijun Ding, Chengrun Yang, Zhao Zhang, Madeleine Udell
Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization for Low-Rank Tensor Completion and Tensor Robust Principal Component Analysis. Trans. Mach. Learn. Res. 2023 (2023)
Manan Tomar, Utkarsh A. Mishra, Amy Zhang, Matthew E. Taylor
Learning Representations for Pixel-based Control: What Matters and Why? Trans. Mach. Learn. Res. 2023 (2023)
Akash Srivastava, Seungwook Han, Kai Xu, Benjamin Rhodes, Michael U. Gutmann
Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression. Trans. Mach. Learn. Res. 2023 (2023)
Juan Miguel Lopez Alcaraz, Nils Strodthoff
Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models. Trans. Mach. Learn. Res. 2023 (2023)
Maurits J. R. Bleeker, Andrew Yates, Maarten de Rijke
Reducing Predictive Feature Suppression in Resource-Constrained Contrastive Image-Caption Retrieval. Trans. Mach. Learn. Res. 2023 (2023)
Matteo Gamba, Erik Englesson, Mårten Björkman, Hossein Azizpour
Deep Double Descent via Smooth Interpolation. Trans. Mach. Learn. Res. 2023 (2023)
Jiaqi Ma, Ziqiao Ma, Joyce Chai, Qiaozhu Mei
Partition-Based Active Learning for Graph Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
Shusheng Xu, Yancheng Liang, Yunfei Li, Simon Shaolei Du, Yi Wu
Beyond Information Gain: An Empirical Benchmark for Low-Switching-Cost Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023)