arXiv:2512.00303v1 Announce Type: new Abstract: Federated reinforcement learning (FRL) enables distributed learning of optimal policies while preserving local data privacy through gradient sharing.However, FRL faces the risk of data privacy leaks, where attackers exploit shared gradients to reconstruct local training…
arXiv:2512.01276v1 Announce Type: cross Abstract: The standard definition of PAC learning (Valiant 1984) requires learners to succeed under all distributions — even ones that are intractable to sample from. This stands in contrast to samplable PAC learning (Blum, Furst, Kearns,…
arXiv:2512.00307v1 Announce Type: new Abstract: Signed graphs with positive and negative edges can model complex relationships in social networks. Leveraging on balance theory that deduces edge signs from multi-hop node pairs, signed graph learning can generate node embeddings that preserve…
arXiv:2512.01485v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) reasoning has significantly advanced the problem-solving capabilities of Large Language Models (LLMs), yet conventional CoT often exhibits internal determinism during decoding, limiting exploration of plausible alternatives. Recent methods attempt to address this by…
arXiv:2512.00311v1 Announce Type: new Abstract: Knowledge Tracing (KT) aims to model student’s knowledge state and predict future performance to enable personalized learning in Intelligent Tutoring Systems. However, traditional KT methods face fundamental limitations in explainability, as they rely solely on…
arXiv:2512.01809v1 Announce Type: cross Abstract: Generative models, like flows and diffusions, have recently emerged as popular and efficacious policy parameterizations in robotics. There has been much speculation as to the factors underlying their successes, ranging from capturing multi-modal action distribution…
arXiv:2512.00321v1 Announce Type: new Abstract: Power consumption has become a critical aspect of modern life due to the consistent reliance on technological advancements. Reducing power consumption or following power usage predictions can lead to lower monthly costs and improved electrical…
arXiv:2305.19659v5 Announce Type: replace Abstract: Subgraph counting is a fundamental task for analyzing structural patterns in graph-structured data, with important applications in domains such as computational biology and social network analysis, where recurring motifs reveal functional and organizational properties. In…
arXiv:2512.00342v1 Announce Type: new Abstract: Real-world intelligence systems usually operate by combining offline learning and online adaptation with highly correlated and non-stationary system data or signals, which, however, has rarely been investigated theoretically in the literature. This paper initiates a…
arXiv:2505.04382v3 Announce Type: replace-cross Abstract: In this work, we address the voice conversion (VC) task using a vector-based interface. To align audio embeddings between speakers, we employ discrete optimal transport mapping. Our evaluation results demonstrate the high quality and effectiveness…
