Extensive experimental evaluation demonstrates that the proposed Context-Aware representations not only provide intrinsic interpretability and dimensionality reduction but also maintain or enhance effectiveness in downstream tasks, specifically in image retrieval and semi-supervised classification using Graph Convolutional Networks (GCNs).
Thiago César Castilho Almeida, Gustavo Rosseto Letício, Vinicius Atsushi Sato Kawai et al.· International Conference on...· 0 citations
GRaCE surpasses RaDE and Original Features across diverse datasets, including textual and image collections, excelling in retrieval, classification, and clustering tasks, considering state-of-the-art Transformer models as feature descriptors and Graph Convolutional Networks models in classification tasks.
Thiago César Castilho Almeida, G. Leticio, L. P. Valem et al.· IEEE International Joint Con...· 1 citation· ⚡1
Voice-to-Trajectory for Air Traffic Control is introduced, a joint voice communication-flight trajectory data embedding framework that can be a component of situational awareness in congested airspaces, and assist the development of tools for ATC as they reason in real-time over Automatic Dependent Surveillance-Broadcast trajectories.
Louis Brusset, Mathurin Petit, J. Kam et al.· 0 citations
Bernard CVaR-UCBVI is minimax-optimal over the full return-law class in the leading-order regime; the lower-order terms retain their $\tau^{-1}$ dependence.
Yuan-Long Chen· 0 citations
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A curious phenomenon called mode connectivity, the ability to connect neural networks in the loss surface, defies explanation entirely is elucidates, explains and exploits this special structure in the loss landscape.
A lightweight defense framework that generically augments optimization methods in the ML pipeline to have significantly-improved empirical privacy on standard benchmarks is given, and it is shown that the framework comes at no theoretical privacy cost when augmenting DP-SGD, unlike previously-proposed defenses against membership inference attacks.
Saloni Modi, Srivi Balaji, Yu-Song Zhu et al.· 0 citations
SemKV preserves every token, ranks tokens by a model-internal score, and assigns two adjacent above-cliff precisions, achieving a measured 6.0x storage reduction with no statistically detectable quality difference from full KV (n=900, three seeds), and outperforming FP16 token pruning granted a 1.5x larger memory budget.
GCC formulates coded computing through a natural end-to-end mean-squared error loss that directly measures the discrepancy between the desired computations and their recovered estimates, and enables theoretical performance guarantees for GCC under two complementary straggler regimes.
Parsa Moradi, B. Tahmasebi, M. Maddah-ali· 0 citations
This work asks a simple question: can the model's own SID tree serve as the action abstraction for that OPE, and explains how resolution depth is the operative knob and a conditional bias bound links the coarsening bias to the quantizer's worst-case reconstruction residual and the target-logging divergence.
The Conservative Hybrid Graph Network (CHGN), which learns routing, regime assignment, and removal rates as data-driven surrogates and inserts them into a fixed transport equation, so that the mass balance holds by construction for any predicted routing.
The mechanism is a halt vector: a difference-of-means direction at layer 18 of this model whose steering strength controls how long it thinks, while a replicated value axis does nothing, and what works is reconstructing the whole steered activation with those dimensions pinned to their natural values.
A weeklong summer workshop brought higher education faculty to campus to explore how AI and machine learning materials can be adapted for their classrooms.
Adaptive AI agents can help make BIM data more machine-readable by navigating IFC models, interpreting inconsistent information, and mapping it to defined standards. In this blog, Alok Rawat shares findings from a real-world pilot in construction workflows. The post Adaptive AI Agents in Construction Workflows appeared first on GPT-Lab.
