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Aitchison Embeddings for Learning Compositional Graph Representations
Published in ArXiv cs.LG Recent Papers (2026)Subjects: “…ArXiv cs.LG Recent Papers…”
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Deep Kernel Learning for Stratifying Glaucoma Trajectories
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FedKPer: Tackling Generalization and Personalization in Medical Federated Learning via Knowledge Personalization
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Adaptive Querying with AI Persona Priors
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Evaluating the Architectural Reasoning Capabilities of LLM Provers via the Obfuscated Natural Number Game
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Augmented Lagrangian Multiplier Network for State-wise Safety in Reinforcement Learning
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Spiking Sequence Machines and Transformers
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Reinforcement Learning with Markov Risk Measures and Multipattern Risk Approximation
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SpecKV: Adaptive Speculative Decoding with Compression-Aware Gamma Selection
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Unsupervised Machine Learning for Detecting Structural Anomalies in European Regional Statistics
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Multi-fidelity surrogates for mechanics of composites: from co-kriging to multi-fidelity neural networks
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Enhancing RL Generalizability in Robotics through SHAP Analysis of Algorithms and Hyperparameters
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Standing on the Shoulders of Giants: Stabilized Knowledge Distillation for Cross--Language Code Clone Detection
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Trust, but Verify: Peeling Low-Bit Transformer Networks for Training Monitoring
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A second-order method on the Stiefel manifold via Newton$unicode{x2013}$Schulz
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A Closed-Form Persistence-Landmark Pipeline for Certified Point-Cloud and Graph Classification
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VideoNet: A Large-Scale Dataset for Domain-Specific Action Recognition
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Fine-Grained Graph Generation through Latent Mixture Scheduling
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A decoupled diffusion planner that adapts to changing cost limits by using cost-conditioned generation for safety and reward gradients for performance
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Universality in Deep Neural Networks: An approach via the Lindeberg exchange principle
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