Europe
Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions
AI/ML problems, and in each such case σ is assumed to be known .
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation
Ruibo Tu, Kun Zhang, Bo Bertilson, Hedvig Kjellstrom, Cheng Zhang
Neural Information Processing Systems http://nips.cc/
High-Fidelity Audio Compression with Improved RVQGAN
Language models have been successfully used to model natural signals, such as images, speech, and music.
Learning from Label Proportions with Generative Adversarial Networks
Jiabin Liu, Bo Wang, Zhiquan Qi, YingJie Tian, Yong Shi
Neural Information Processing Systems http://nips.cc/
Learning sparse neural networks via sensitivity-driven regularization
Enzo Tartaglione, Skjalg Lepsøy, Attilio Fiandrotti, Gianluca Francini
Neural Information Processing Systems http://nips.cc/
Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning
Akihiro Kishimoto, Beat Buesser, Bei Chen, Adi Botea
Search is a core AI technique, especially in games [5, 27, 31] and domain-independent planning [3,12].
TowardsBetterEvaluationfor DynamicLinkPrediction
Despite the prevalence ofrecent success inlearning from static graphs, learning from time-evolving graphs remains an open challenge.
DAC: The Double Actor-Critic Architecture for Learning Options
Shangtong Zhang, Shimon Whiteson
Neural Information Processing Systems http://nips.cc/
L VM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching Duy M. H. Nguyen
Obtaining large pre-trained models that can be fine-tuned to new tasks with limited annotated samples has remained an open challenge for medical imaging data.