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cs.LG updates on arXiv.org

Memory-Guided Trust-Region Bayesian Optimization (MG-TuRBO) for High Dimensions EngageTriBoost: Predictive Modeling of User Engagement in Digital Mental Health Intervention Using Explainable Machine Learning Reservoir observer enhanced with residual calibration and attention mechanism Creator Incentives in Recommender Systems: A Cooperative Game-Theoretic Approach for Stable and Fair Collaboration in Multi-Agent Bandits Efficient RL Training for LLMs with Experience Replay Wireless Communication Enhanced Value Decomposition for Multi-Agent Reinforcement Learning A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Adversarial Sensor Errors for Safe and Robust Wind Turbine Fleet Control IKKA: Inversion Classification via Critical Anomalies for Robust Visual Servoing Adaptive Simulation Experiment for LLM Policy Optimization EvoLen: Evolution-Guided Tokenization for DNA Language Model Smartwatch-Based Sitting Time Estimation in Real-World Office Settings Structural Evaluation Metrics for SVG Generation via Leave-One-Out Analysis Loom: A Scalable Analytical Neural Computer Architecture Hierarchical Kernel Transformer: Multi-Scale Attention with an Information-Theoretic Approximation Analysis Spectral Geometry of LoRA Adapters Encodes Training Objective and Predicts Harmful Compliance Finite-Sample Analysis of Nonlinear Independent Component Analysis:Sample Complexity and Identifiability Bounds How does Chain of Thought decompose complex tasks? Uncertainty-Aware Transformers: Conformal Prediction for Language Models Adaptive Candidate Point Thompson Sampling for High-Dimensional Bayesian Optimization Using Synthetic Data for Machine Learning-based Childhood Vaccination Prediction in Narok, Kenya Delve into the Applicability of Advanced Optimizers for Multi-Task Learning Bridging SFT and RL: Dynamic Policy Optimization for Robust Reasoning Multi-Agent Decision-Focused Learning via Value-Aware Sequential Communication Predictive Entropy Links Calibration and Paraphrase Sensitivity in Medical Vision-Language Models Efficient Hierarchical Implicit Flow Q-learning for Offline Goal-conditioned Reinforcement Learning Modality-Aware Zero-Shot Pruning and Sparse Attention for Efficient Multimodal Edge Inference The nextAI Solution to the NeurIPS 2023 LLM Efficiency Challenge Feature-Label Modal Alignment for Robust Partial Multi-Label Learning Integrated electro-optic attention nonlinearities for transformers Toward World Models for Epidemiology Tracing the Chain: Deep Learning for Stepping-Stone Intrusion Detection Policy-Aware Design of Large-Scale Factorial Experiments Beyond Augmented-Action Surrogates for Multi-Expert Learning-to-Defer Continuous Orthogonal Mode Decomposition: Haptic Signal Prediction in Tactile Internet FIT-GNN: Faster Inference Time for GNNs that 'FIT' in Memory Using Coarsening Batch Distillation Data for Developing Machine Learning Anomaly Detection Methods Predicting Metabolic Dysfunction-Associated Steatotic Liver Disease using Machine Learning Methods: A Retrospective Cohort Study Adaptive Tuning of Parameterized Traffic Controllers via Multi-Agent Reinforcement Learning Bandwidth-constrained Variational Message Encoding for Cooperative Multi-agent Reinforcement Learning Neural Two-Stage Stochastic Optimization for Solving Unit Commitment Problem SafeAdapt: Provably Safe Policy Updates in Deep Reinforcement Learning Rays as Pixels: Learning A Joint Distribution of Videos and Camera Trajectories PhysInOne: Visual Physics Learning and Reasoning in One Suite FIRE-CIR: Fine-grained Reasoning for Composed Fashion Image Retrieval Detecting Diffusion-generated Images via Dynamic Assembly Forests PDE-regularized Dynamics-informed Diffusion with Uncertainty-aware Filtering for Long-Horizon Dynamics Leave My Images Alone: Preventing Multi-Modal Large Language Models from Analyzing Images via Visual Prompt Injection Regime-Conditional Retrieval: Theory and a Transferable Router for Two-Hop QA Identification and Anonymization of Named Entities in Unstructured Information Sources for Use in Social Engineering Detection Hypergraph Neural Networks Accelerate MUS Enumeration ASTRA: Adaptive Semantic Tree Reasoning Architecture for Complex Table Question Answering Neighbourhood Transformer: Switchable Attention for Monophily-Aware Graph Learning WOMBET: World Model-Based Experience Transfer for Robust and Sample-efficient Reinforcement Learning Low-Data Supervised Adaptation Outperforms Prompting for Cloud Segmentation Under Domain Shift Revisiting the Capacity Gap in Chain-of-Thought Distillation from a Practical Perspective A Mathematical Framework for Temporal Modeling and Counterfactual Policy Simulation of Student Dropout Temporal Dropout Risk in Learning Analytics: A Harmonized Survival Benchmark Across Dynamic and Early-Window Representations MedFormer-UR: Uncertainty-Routed Transformer for Medical Image Classification Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs Post-Hoc Guidance for Consistency Models by Joint Flow Distribution Learning SenBen: Sensitive Scene Graphs for Explainable Content Moderation R2G: A Multi-View Circuit Graph Benchmark Suite from RTL to GDSII $p1$: Better Prompt Optimization with Fewer Prompts Deep Learning-Based Tracking and Lineage Reconstruction of Ligament Breakup Every Response Counts: Quantifying Uncertainty of LLM-based Multi-Agent Systems through Tensor Decomposition Unified Multimodal Uncertain Inference EfficientSign: An Attention-Enhanced Lightweight Architecture for Indian Sign Language Recognition Skip-Connected Policy Optimization for Implicit Advantage PRAGMA: Revolut Foundation Model 3D-VCD: Hallucination Mitigation in 3D-LLM Embodied Agents through Visual Contrastive Decoding Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation StructRL: Recovering Dynamic Programming Structure from Learning Dynamics in Distributional Reinforcement Learning Generative 3D Gaussian Splatting for Arbitrary-ResolutionAtmospheric Downscaling and Forecasting From Selection to Scheduling: Federated Geometry-Aware Correction Makes Exemplar Replay Work Better under Continual Dynamic Heterogeneity Needle in a Haystack: One-Class Representation Learning for Detecting Rare Malignant Cells in Computational Cytology Detection of Hate and Threat in Digital Forensics: A Case-Driven Multimodal Approach Semantic Intent Fragmentation: A Single-Shot Compositional Attack on Multi-Agent AI Pipelines Joint Interference Detection and Identification via Adversarial Multi-task Learning HaloProbe: Bayesian Detection and Mitigation of Object Hallucinations in Vision-Language Models R3PM-Net: Real-time, Robust, Real-world Point Matching Network From Dispersion to Attraction: Spectral Dynamics of Hallucination Across Whisper Model Scales AlphaLab: Autonomous Multi-Agent Research Across Optimization Domains with Frontier LLMs Act or Escalate? Evaluating Escalation Behavior in Automation with Language Models Multivariate Time Series Anomaly Detection via Dual-Branch Reconstruction and Autoregressive Flow-based Residual Density Estimation On the Spectral Geometry of Cross-Modal Representations: A Functional Map Diagnostic for Multimodal Alignment Structured Exploration and Exploitation of Label Functions for Automated Data Annotation MolPaQ: Modular Quantum-Classical Patch Learning for Interpretable Molecular Generation CausalVAD: De-confounding End-to-End Autonomous Driving via Causal Intervention Reinforcement-aware Knowledge Distillation for LLM Reasoning SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework A Horizon-Aware Decision-Support Framework for Demand Forecasting Model Selection in Resilient Production Planning Measurement-Consistent Langevin Corrector for Stabilizing Latent Diffusion Inverse Problem Solvers Multi-agent Adaptive Mechanism Design When & How to Write for Personalized Demand-aware Query Rewriting in Video Search Relational Visual Similarity From Navigation to Refinement: Revealing the Two-Stage Nature of Flow-based Diffusion Models through Oracle Velocity On-the-Fly Adaptation to Quantization: Configuration-Aware LoRA for Efficient Fine-Tuning of Quantized LLMs STCast: Adaptive Boundary Alignment for Global and Regional Weather Forecasting OmniPrism: Learning Disentangled Visual Concept for Image Generation
Initialization-Dependent Sample Complexity of Linear Predictors and Neural Networks
Roey Magen, Ohad Shamir · 2023-05-26 · via cs.LG updates on arXiv.org

We provide several new results on the sample complexity of vector-valued linear predictors (parameterized by a matrix), and more generally neural networks. Focusing on size-independent bounds, where only the Frobenius norm distance of the parameters from some fixed reference matrix $W_0$ is controlled, we show that the sample complexity behavior can be surprisingly different than what we may expect considering the well-studied setting of scalar-valued linear predictors. This also leads to new sample complexity bounds for feed-forward neural networks, tackling some open questions in the literature, and establishing a new convex linear prediction problem that is provably learnable without uniform convergence.

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