Learning After Model Deployment
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Kaymak, Derda, Kim, Gyuhak, Kaichi, Tomoya, Konishi, Tatsuya, Liu, Bing |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Open-World Continual Learning: Unifying Novelty Detection and Continual Learning
par: Kim, Gyuhak, et autres
Publié: (2023)
par: Kim, Gyuhak, et autres
Publié: (2023)
CADE: Continual Weakly-supervised Video Anomaly Detection with Ensembles
par: Hashimoto, Satoshi, et autres
Publié: (2025)
par: Hashimoto, Satoshi, et autres
Publié: (2025)
SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models
par: Kim, Gyuhak, et autres
Publié: (2025)
par: Kim, Gyuhak, et autres
Publié: (2025)
Comprehensive Deployment-Oriented Assessment for Cross-Environment Generalization in Deep Learning-Based mmWave Radar Sensing
par: Tanaka, Tomoya, et autres
Publié: (2025)
par: Tanaka, Tomoya, et autres
Publié: (2025)
Multi-objective Reinforcement Learning With Augmented States Requires Rewards After Deployment
par: Vamplew, Peter, et autres
Publié: (2026)
par: Vamplew, Peter, et autres
Publié: (2026)
Batch Acquisition Function Evaluations and Decouple Optimizer Updates for Faster Bayesian Optimization
par: Irie, Kaichi, et autres
Publié: (2025)
par: Irie, Kaichi, et autres
Publié: (2025)
Interpretable Fuzzy Systems For Forward Osmosis Desalination
par: Khaled, Qusai, et autres
Publié: (2026)
par: Khaled, Qusai, et autres
Publié: (2026)
In-Context Learning Is Provably Bayesian Inference: A Generalization Theory for Meta-Learning
par: Wakayama, Tomoya, et autres
Publié: (2025)
par: Wakayama, Tomoya, et autres
Publié: (2025)
Deploying Large AI Models on Resource-Limited Devices with Split Federated Learning
par: Qiang, Xianke, et autres
Publié: (2025)
par: Qiang, Xianke, et autres
Publié: (2025)
Learned Neighbor Trust for Collaborative Deployment in Model-Agnostic Decentralized Learning
par: Lanier, Michael, et autres
Publié: (2026)
par: Lanier, Michael, et autres
Publié: (2026)
On-Demand Model and Client Deployment in Federated Learning with Deep Reinforcement Learning
par: Chahoud, Mario, et autres
Publié: (2024)
par: Chahoud, Mario, et autres
Publié: (2024)
Explainable Uncertainty Quantification for Wastewater Treatment Energy Prediction via Interval Type-2 Neuro-Fuzzy System
par: Khaled, Qusai, et autres
Publié: (2026)
par: Khaled, Qusai, et autres
Publié: (2026)
Explorative Curriculum Learning for Strongly Correlated Electron Systems
par: Yamazaki, Kimihiro, et autres
Publié: (2025)
par: Yamazaki, Kimihiro, et autres
Publié: (2025)
Learning from Similarity/Dissimilarity and Pairwise Comparison
par: Tate, Tomoya, et autres
Publié: (2026)
par: Tate, Tomoya, et autres
Publié: (2026)
Bayesian Inference for Consistent Predictions in Overparameterized Nonlinear Regression
par: Wakayama, Tomoya
Publié: (2024)
par: Wakayama, Tomoya
Publié: (2024)
Automated Reinforcement Learning: An Overview
par: Afshar, Reza Refaei, et autres
Publié: (2022)
par: Afshar, Reza Refaei, et autres
Publié: (2022)
Learning Functional Graphs with Nonlinear Sufficient Dimension Reduction
par: Kim, Kyongwon, et autres
Publié: (2026)
par: Kim, Kyongwon, et autres
Publié: (2026)
Discovering Multiple Solutions from a Single Task in Offline Reinforcement Learning
par: Osa, Takayuki, et autres
Publié: (2024)
par: Osa, Takayuki, et autres
Publié: (2024)
Learning Koopman operators for coupled systems via information on governing equations of subsystems
par: Naoi, Tatsuya, et autres
Publié: (2026)
par: Naoi, Tatsuya, et autres
Publié: (2026)
Reinforcement Learning for Machine Learning Model Deployment: Evaluating Multi-Armed Bandits in ML Ops Environments
par: McClendon, S. Aaron, et autres
Publié: (2025)
par: McClendon, S. Aaron, et autres
Publié: (2025)
Strategically Deceptive Model Deployment in Performative Prediction
par: Bautiste, Javier Sanguino, et autres
Publié: (2025)
par: Bautiste, Javier Sanguino, et autres
Publié: (2025)
Learning the Simplest Neural ODE
par: Okamoto, Yuji, et autres
Publié: (2025)
par: Okamoto, Yuji, et autres
Publié: (2025)
Bayesian Analysis for Over-parameterized Linear Model via Effective Spectra
par: Wakayama, Tomoya, et autres
Publié: (2023)
par: Wakayama, Tomoya, et autres
Publié: (2023)
SLMQuant:Benchmarking Small Language Model Quantization for Practical Deployment
par: Wang, Jiacheng, et autres
Publié: (2025)
par: Wang, Jiacheng, et autres
Publié: (2025)
Achieving Upper Bound Accuracy of Joint Training in Continual Learning
par: Momeni, Saleh, et autres
Publié: (2025)
par: Momeni, Saleh, et autres
Publié: (2025)
Automating the Training and Deployment of Models in MLOps by Integrating Systems with Machine Learning
par: Liang, Penghao, et autres
Publié: (2024)
par: Liang, Penghao, et autres
Publié: (2024)
Reliably Detecting Model Failures in Deployment Without Labels
par: Nguyen, Viet, et autres
Publié: (2025)
par: Nguyen, Viet, et autres
Publié: (2025)
Models Know Their Shortcuts: Deployment-Time Shortcut Mitigation
par: Li, Jiayi, et autres
Publié: (2026)
par: Li, Jiayi, et autres
Publié: (2026)
BitRL: Reinforcement Learning with 1-bit Quantized Language Models for Resource-Constrained Edge Deployment
par: Sajid, Md. Ashiq Ul Islam, et autres
Publié: (2026)
par: Sajid, Md. Ashiq Ul Islam, et autres
Publié: (2026)
AutoTailor: Automatic and Efficient Adaptive Model Deployment for Diverse Edge Devices
par: Liu, Mengyang, et autres
Publié: (2025)
par: Liu, Mengyang, et autres
Publié: (2025)
Comparative Field Deployment of Reinforcement Learning and Model Predictive Control for Residential HVAC
par: Mulayim, Ozan Baris, et autres
Publié: (2025)
par: Mulayim, Ozan Baris, et autres
Publié: (2025)
Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment
par: Ahmed, Shibbir, et autres
Publié: (2024)
par: Ahmed, Shibbir, et autres
Publié: (2024)
ML2SC: Deploying Machine Learning Models as Smart Contracts on the Blockchain
par: Li, Zhikai, et autres
Publié: (2024)
par: Li, Zhikai, et autres
Publié: (2024)
How to Evaluate Participant Contributions in Decentralized Federated Learning
par: Anada, Honoka, et autres
Publié: (2025)
par: Anada, Honoka, et autres
Publié: (2025)
Deployment-complete benchmarking
par: Mansouri, El Mustapha, et autres
Publié: (2026)
par: Mansouri, El Mustapha, et autres
Publié: (2026)
Ensemble Prediction via Covariate-dependent Stacking
par: Wakayama, Tomoya, et autres
Publié: (2024)
par: Wakayama, Tomoya, et autres
Publié: (2024)
Frontiers of Deep Learning: From Novel Application to Real-World Deployment
par: Xie, Rui
Publié: (2024)
par: Xie, Rui
Publié: (2024)
Bridging the Resource Gap: Deploying Advanced Imitation Learning Models onto Affordable Embedded Platforms
par: Ge, Haizhou, et autres
Publié: (2024)
par: Ge, Haizhou, et autres
Publié: (2024)
Rescaling-Aware Training for Efficient Deployment of Deep Learning Models on Full-Integer Hardware
par: Mueller, Lion, et autres
Publié: (2025)
par: Mueller, Lion, et autres
Publié: (2025)
Quantum Tunneling-Aware Machine Learning: Physics-Derived Noise Models for Robust Deployment
par: Hwang, Uiwon, et autres
Publié: (2026)
par: Hwang, Uiwon, et autres
Publié: (2026)
Documents similaires
-
Open-World Continual Learning: Unifying Novelty Detection and Continual Learning
par: Kim, Gyuhak, et autres
Publié: (2023) -
CADE: Continual Weakly-supervised Video Anomaly Detection with Ensembles
par: Hashimoto, Satoshi, et autres
Publié: (2025) -
SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models
par: Kim, Gyuhak, et autres
Publié: (2025) -
Comprehensive Deployment-Oriented Assessment for Cross-Environment Generalization in Deep Learning-Based mmWave Radar Sensing
par: Tanaka, Tomoya, et autres
Publié: (2025) -
Multi-objective Reinforcement Learning With Augmented States Requires Rewards After Deployment
par: Vamplew, Peter, et autres
Publié: (2026)