Image de couverture de livre

Optimizing Rank-based Metrics with Blackbox Differentiation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Rolínek, Michal, Musil, Vít, Paulus, Anselm, Vlastelica, Marin, Michaelis, Claudio, Martius, Georg
Format:	Preprint
Publié:	2019
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Differentiation of Blackbox Combinatorial Solvers
par: Vlastelica, Marin, et autres
Publié: (2019)

Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers
par: Rolínek, Michal, et autres
Publié: (2020)

CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints
par: Paulus, Anselm, et autres
Publié: (2021)

LPGD: A General Framework for Backpropagation through Embedded Optimization Layers
par: Paulus, Anselm, et autres
Publié: (2024)

Backpropagation through Combinatorial Algorithms: Identity with Projection Works
par: Sahoo, Subham Sekhar, et autres
Publié: (2022)

SoftJAX & SoftTorch: Empowering Automatic Differentiation Libraries with Informative Gradients
par: Paulus, Anselm, et autres
Publié: (2026)

Differentiable Simulation of Hard Contacts with Soft Gradients for Learning and Control
par: Paulus, Anselm, et autres
Publié: (2025)

Dual-Force: Enhanced Offline Diversity Maximization under Imitation Constraints
par: Kolev, Pavel, et autres
Publié: (2025)

Offline Diversity Maximization Under Imitation Constraints
par: Vlastelica, Marin, et autres
Publié: (2023)

Epistemically-guided forward-backward exploration
par: Urpí, Núria Armengol, et autres
Publié: (2025)

Causal Action Influence Aware Counterfactual Data Augmentation
par: Urpí, Núria Armengol, et autres
Publié: (2024)

Novel Algorithms for Smoothly Differentiable and Efficiently Vectorizable Contact Manifold Construction
par: Beker, Onur, et autres
Publié: (2026)

Optimistic Task Inference for Behavior Foundation Models
par: Rupf, Thomas, et autres
Publié: (2025)

Preference-Optimized Pareto Set Learning for Blackbox Optimization
par: Haishan, Zhang, et autres
Publié: (2024)

Colored Noise in PPO: Improved Exploration and Performance through Correlated Action Sampling
par: Hollenstein, Jakob, et autres
Publié: (2023)

Directed Exploration in Reinforcement Learning from Linear Temporal Logic
par: Bagatella, Marco, et autres
Publié: (2024)

Rethinking Prompt Optimization: Reinforcement, Diversification, and Migration in Blackbox LLMs
par: Davari, MohammadReza, et autres
Publié: (2025)

Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning
par: De Santi, Riccardo, et autres
Publié: (2025)

Outline of an Independent Systematic Blackbox Test for ML-based Systems
par: Wiesbrock, Hans-Werner, et autres
Publié: (2024)

Soft Forward-Backward Representations for Zero-shot Reinforcement Learning with General Utilities
par: Bagatella, Marco, et autres
Publié: (2026)

Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities
par: Zadaianchuk, Andrii, et autres
Publié: (2023)

Active Fine-Tuning of Multi-Task Policies
par: Bagatella, Marco, et autres
Publié: (2024)

Offline vs. Online Learning in Model-based RL: Lessons for Data Collection Strategies
par: Chen, Jiaqi, et autres
Publié: (2025)

Scaling Laws and Tradeoffs in Recurrent Networks of Expressive Neurons
par: Spieler, Aaron, et autres
Publié: (2026)

Test-time Offline Reinforcement Learning on Goal-related Experience
par: Bagatella, Marco, et autres
Publié: (2025)

Zero-Shot Offline Imitation Learning via Optimal Transport
par: Rupf, Thomas, et autres
Publié: (2024)

Smoothly Differentiable and Efficiently Vectorizable Contact Manifold Generation
par: Beker, Onur, et autres
Publié: (2026)

Provable Maximum Entropy Manifold Exploration via Diffusion Models
par: De Santi, Riccardo, et autres
Publié: (2025)

Blackbox Model Provenance via Palimpsestic Membership Inference
par: Kuditipudi, Rohith, et autres
Publié: (2025)

AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs
par: Paulus, Anselm, et autres
Publié: (2024)

Forecasting in Offline Reinforcement Learning for Non-stationary Environments
par: Ada, Suzan Ece, et autres
Publié: (2025)

Whispering to a Blackbox: Bootstrapping Frozen OCR with Visual Prompts
par: Samandarov, Samandar, et autres
Publié: (2026)

Learning 3D-Gaussian Simulators from RGB Videos
par: Zhobro, Mikel, et autres
Publié: (2025)

GASP: Guided Asymmetric Self-Play For Coding LLMs
par: Jana, Swadesh, et autres
Publié: (2026)

Stochastic Decision Horizons for Constrained Reinforcement Learning
par: Milosevic, Nikola, et autres
Publié: (2026)

Improving Structural Diversity of Blackbox LLMs via Chain-of-Specification Prompting
par: Young, Halley, et autres
Publié: (2024)

Fault Detection in Solar Thermal Systems using Probabilistic Reconstructions
par: Ebmeier, Florian, et autres
Publié: (2025)

Identifying Terrain Physical Parameters from Vision -- Towards Physical-Parameter-Aware Locomotion and Navigation
par: Chen, Jiaqi, et autres
Publié: (2024)

Drifting Fields are not Conservative
par: Franz, Leonard T., et autres
Publié: (2026)

Pessimistic Off-Policy Optimization for Learning to Rank
par: Cief, Matej, et autres
Publié: (2022)