:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Tang, Sunbochen, Goertzen, Andrea, Azizan, Navid
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	https://arxiv.org/abs/2604.05374
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

ECO: Energy-Constrained Operator Learning for Chaotic Dynamics with Boundedness Guarantees
por: Goertzen, Andrea, et al.
Publicado: (2025)

HardNet++: Nonlinear Constraint Enforcement in Neural Networks
por: Goertzen, Andrea, et al.
Publicado: (2026)

Reverse Flow Matching: A Unified Framework for Online Reinforcement Learning with Diffusion and Flow Policies
por: Li, Zeyang, et al.
Publicado: (2026)

HardNet: Hard-Constrained Neural Networks with Universal Approximation Guarantees
por: Min, Youngjae, et al.
Publicado: (2024)

Meta-Learning for Adaptive Control with Automated Mirror Descent
por: Tang, Sunbochen, et al.
Publicado: (2024)

Learning Dissipative Chaotic Dynamics with Boundedness Guarantees
por: Tang, Sunbochen, et al.
Publicado: (2024)

HardFlow: Hard-Constrained Sampling for Flow-Matching Models via Trajectory Optimization
por: Li, Zeyang, et al.
Publicado: (2025)

Constrained Online Decision-Making: A Unified Framework
por: Hu, Haichen, et al.
Publicado: (2025)

On the Role of Transformer Feed-Forward Layers in Nonlinear In-Context Learning
por: Sun, Haoyuan, et al.
Publicado: (2025)

Safe Multi-Agent Reinforcement Learning with Convergence to Generalized Nash Equilibrium
por: Li, Zeyang, et al.
Publicado: (2024)

Personalized Collaborative Learning with Affinity-Based Variance Reduction
por: Zhang, Chenyu, et al.
Publicado: (2025)

ORFit: One-Pass Learning via Bridging Orthogonal Gradient Descent and Recursive Least-Squares
por: Min, Youngjae, et al.
Publicado: (2022)

A Unified Approach to Controlling Implicit Regularization via Mirror Descent
por: Sun, Haoyuan, et al.
Publicado: (2023)

Differentially Private Synthetic Data Generation for Relational Databases
por: Alimohammadi, Kaveh, et al.
Publicado: (2024)

Online Learning for Equilibrium Pricing in Markets under Incomplete Information
por: Jalota, Devansh, et al.
Publicado: (2023)

Efficient Multi-Adapter LLM Serving via Cross-Model KV-Cache Reuse with Activated LoRA
por: Li, Allison, et al.
Publicado: (2025)

SketchOGD: Memory-Efficient Continual Learning
por: Min, Youngjae, et al.
Publicado: (2023)

A Comparative Analysis of Distributed Linear Solvers under Data Heterogeneity
por: Velasevic, Boris, et al.
Publicado: (2023)

Optimizing Attention with Mirror Descent: Generalized Max-Margin Token Selection
por: Julistiono, Addison Kristanto, et al.
Publicado: (2024)

Tractable Uncertainty-Aware Meta-Learning
por: Park, Young-Jin, et al.
Publicado: (2022)

Quantifying Representation Reliability in Self-Supervised Learning Models
por: Park, Young-Jin, et al.
Publicado: (2023)

Differentiable Multiphysics Co-Optimization via Implicit Neural Representations: A Transient Hamburger-Cooking Benchmark
por: Zobeiry, Navid
Publicado: (2026)

Projected Neural Differential Equations for Learning Constrained Dynamics
por: White, Alistair, et al.
Publicado: (2024)

DisjunctiveNet: Neural Symbolic Learning via Differentiable Convexified Optimization Layers
por: Pal, Shraman, et al.
Publicado: (2026)

Know What You Don't Know: Uncertainty Calibration of Process Reward Models
por: Park, Young-Jin, et al.
Publicado: (2025)

DAE-HardNet: A Physics Constrained Neural Network Enforcing Differential-Algebraic Hard Constraints
por: Golder, Rahul, et al.
Publicado: (2025)

Representing Neural Network Layers as Linear Operations via Koopman Operator Theory
por: Aswani, Nishant Suresh, et al.
Publicado: (2024)

NeuralMatrix: Compute the Entire Neural Networks with Linear Matrix Operations for Efficient Inference
por: Sun, Ruiqi, et al.
Publicado: (2023)

Differentiable Zero-One Loss via Hypersimplex Projections
por: Gomez, Camilo, et al.
Publicado: (2026)

Random Linear Projections Loss for Hyperplane-Based Optimization in Neural Networks
por: Venkatasubramanian, Shyam, et al.
Publicado: (2023)

SnareNet: Flexible Repair Layers for Neural Networks with Hard Constraints
por: Chu, Ya-Chi, et al.
Publicado: (2026)

On Generalization Bounds for Neural Networks with Low Rank Layers
por: Pinto, Andrea, et al.
Publicado: (2024)

Hierarchical Stochastic Differential Equation Models for Latent Manifold Learning in Neural Time Series
por: Rajaei, Pedram, et al.
Publicado: (2025)

Fractional-order Jacobian Matrix Differentiation and Its Application in Artificial Neural Networks
por: zhou, Xiaojun, et al.
Publicado: (2025)

Matrix Manifold Neural Networks++
por: Nguyen, Xuan Son, et al.
Publicado: (2024)

Enhancing Adversarial Robustness of Deep Neural Networks Through Supervised Contrastive Learning
por: Wang, Longwei, et al.
Publicado: (2024)

Random Neural Network Expressivity for Non-Linear Partial Differential Equations
por: Mehmood, Muhammed Ali, et al.
Publicado: (2026)

ENFORCE: Nonlinear Constrained Learning with Adaptive-depth Neural Projection
por: Lastrucci, Giacomo, et al.
Publicado: (2025)

LUNA: Linear Universal Neural Attention with Generalization Guarantees
por: Shahbazi, Ashkan, et al.
Publicado: (2025)

Linearly Constrained Weights: Reducing Activation Shift for Faster Training of Neural Networks
por: Kutsuna, Takuro
Publicado: (2024)