CANDID DAC: Leveraging Coupled Action Dimensions with Importance Differences in DAC
Fuente:
arXiv
Saved in:
| Main Authors: | Bordne, Philipp, Hasan, M. Asif, Bergman, Eddie, Awad, Noor, Biedenkapp, André |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Inferring Behavior-Specific Context Improves Zero-Shot Generalization in Reinforcement Learning
by: Ndir, Tidiane Camaret, et al.
Published: (2024)
by: Ndir, Tidiane Camaret, et al.
Published: (2024)
A Llama walks into the 'Bar': Efficient Supervised Fine-Tuning for Legal Reasoning in the Multi-state Bar Exam
by: Fernandes, Rean, et al.
Published: (2025)
by: Fernandes, Rean, et al.
Published: (2025)
Hierarchical Transformers are Efficient Meta-Reinforcement Learners
by: Shala, Gresa, et al.
Published: (2024)
by: Shala, Gresa, et al.
Published: (2024)
On the Generalization of Data-Assisted Control in port-Hamiltonian Systems (DAC-pH)
by: Eslami, Mostafa, et al.
Published: (2025)
by: Eslami, Mostafa, et al.
Published: (2025)
Dreaming of Many Worlds: Learning Contextual World Models Aids Zero-Shot Generalization
by: Prasanna, Sai, et al.
Published: (2024)
by: Prasanna, Sai, et al.
Published: (2024)
DAC-LoRA: Dynamic Adversarial Curriculum for Efficient and Robust Few-Shot Adaptation
by: Umrajkar, Ved
Published: (2025)
by: Umrajkar, Ved
Published: (2025)
SegDAC: Visual Generalization in Reinforcement Learning via Dynamic Object Tokens
by: Brown, Alexandre, et al.
Published: (2025)
by: Brown, Alexandre, et al.
Published: (2025)
One-shot World Models Using a Transformer Trained on a Synthetic Prior
by: Ferreira, Fabio, et al.
Published: (2024)
by: Ferreira, Fabio, et al.
Published: (2024)
Speeding Up Multi-Objective Hyperparameter Optimization by Task Similarity-Based Meta-Learning for the Tree-Structured Parzen Estimator
by: Watanabe, Shuhei, et al.
Published: (2022)
by: Watanabe, Shuhei, et al.
Published: (2022)
FairPFN: Transformers Can do Counterfactual Fairness
by: Robertson, Jake, et al.
Published: (2024)
by: Robertson, Jake, et al.
Published: (2024)
Contextual Intelligence The Next Leap for Reinforcement Learning
by: Biedenkapp, André
Published: (2026)
by: Biedenkapp, André
Published: (2026)
On the Importance of Pretraining Data Alignment for Atomic Property Prediction
by: Ghunaim, Yasir, et al.
Published: (2025)
by: Ghunaim, Yasir, et al.
Published: (2025)
Leveraging Constraint Violation Signals For Action-Constrained Reinforcement Learning
by: Brahmanage, Janaka Chathuranga, et al.
Published: (2025)
by: Brahmanage, Janaka Chathuranga, et al.
Published: (2025)
An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework
by: Ghanim, Jihan, et al.
Published: (2024)
by: Ghanim, Jihan, et al.
Published: (2024)
When LLM Judge Scores Look Good but Best-of-N Decisions Fail
by: Landesberg, Eddie
Published: (2026)
by: Landesberg, Eddie
Published: (2026)
Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer
by: Wu, Yulun, et al.
Published: (2025)
by: Wu, Yulun, et al.
Published: (2025)
An Explainable Machine Learning Framework for the Accurate Diagnosis of Ovarian Cancer
by: Newaz, Asif, et al.
Published: (2023)
by: Newaz, Asif, et al.
Published: (2023)
Beyond Eviction Prediction: Leveraging Local Spatiotemporal Public Records to Inform Action
by: Mashiat, Tasfia, et al.
Published: (2024)
by: Mashiat, Tasfia, et al.
Published: (2024)
Don't Waste Your Time: Early Stopping Cross-Validation
by: Bergman, Edward, et al.
Published: (2024)
by: Bergman, Edward, et al.
Published: (2024)
An Analysis of Action-Value Temporal-Difference Methods That Learn State Values
by: Daley, Brett, et al.
Published: (2025)
by: Daley, Brett, et al.
Published: (2025)
iCost: A Novel Instance Complexity Based Cost-Sensitive Learning Framework
by: Newaz, Asif, et al.
Published: (2024)
by: Newaz, Asif, et al.
Published: (2024)
DiabetesNet: A Deep Learning Approach to Diabetes Diagnosis
by: Zhang, Zeyu, et al.
Published: (2024)
by: Zhang, Zeyu, et al.
Published: (2024)
Learning Action Embeddings for Off-Policy Evaluation
by: Cief, Matej, et al.
Published: (2023)
by: Cief, Matej, et al.
Published: (2023)
Importance Sampling for Nonlinear Models
by: Rajmohan, Prakash Palanivelu, et al.
Published: (2025)
by: Rajmohan, Prakash Palanivelu, et al.
Published: (2025)
On The Potential of The Fractal Geometry and The CNNs Ability to Encode it
by: Zini, Julia El, et al.
Published: (2024)
by: Zini, Julia El, et al.
Published: (2024)
Fast Benchmarking of Asynchronous Multi-Fidelity Optimization on Zero-Cost Benchmarks
by: Watanabe, Shuhei, et al.
Published: (2024)
by: Watanabe, Shuhei, et al.
Published: (2024)
Modular Delta Merging with Orthogonal Constraints: A Scalable Framework for Continual and Reversible Model Composition
by: Khan, Haris, et al.
Published: (2025)
by: Khan, Haris, et al.
Published: (2025)
sDAC -- Semantic Digital Analog Converter for Semantic Communications
by: Bao, Zhicheng, et al.
Published: (2024)
by: Bao, Zhicheng, et al.
Published: (2024)
Beyond Training: Optimizing Reinforcement Learning Based Job Shop Scheduling Through Adaptive Action Sampling
by: de Puiseau, Constantin Waubert, et al.
Published: (2024)
by: de Puiseau, Constantin Waubert, et al.
Published: (2024)
Probing the Embedding Space of Transformers via Minimal Token Perturbations
by: Conti, Eddie, et al.
Published: (2025)
by: Conti, Eddie, et al.
Published: (2025)
Low Variance Off-policy Evaluation with State-based Importance Sampling
by: Bossens, David M., et al.
Published: (2022)
by: Bossens, David M., et al.
Published: (2022)
TIP: Token Importance in On-Policy Distillation
by: Xu, Yuanda, et al.
Published: (2026)
by: Xu, Yuanda, et al.
Published: (2026)
The Importance of Time in Causal Algorithmic Recourse
by: Beretta, Isacco, et al.
Published: (2023)
by: Beretta, Isacco, et al.
Published: (2023)
Why Do Language Model Agents Whistleblow?
by: Agrawal, Kushal, et al.
Published: (2025)
by: Agrawal, Kushal, et al.
Published: (2025)
From SHAP Scores to Feature Importance Scores
by: Letoffe, Olivier, et al.
Published: (2024)
by: Letoffe, Olivier, et al.
Published: (2024)
ESPO: Entropy Importance Sampling Policy Optimization
by: Sheng, Yuepeng, et al.
Published: (2025)
by: Sheng, Yuepeng, et al.
Published: (2025)
AIS: Adaptive Importance Sampling for Quantized RL
by: Zhou, Jiajun, et al.
Published: (2026)
by: Zhou, Jiajun, et al.
Published: (2026)
Beyond Distribution Sharpening: The Importance of Task Rewards
by: Mittal, Sarthak, et al.
Published: (2026)
by: Mittal, Sarthak, et al.
Published: (2026)
GIPO: Gaussian Importance Sampling Policy Optimization
by: Lu, Chengxuan, et al.
Published: (2026)
by: Lu, Chengxuan, et al.
Published: (2026)
Features that Make a Difference: Leveraging Gradients for Improved Dictionary Learning
by: Olmo, Jeffrey, et al.
Published: (2024)
by: Olmo, Jeffrey, et al.
Published: (2024)
Similar Items
-
Inferring Behavior-Specific Context Improves Zero-Shot Generalization in Reinforcement Learning
by: Ndir, Tidiane Camaret, et al.
Published: (2024) -
A Llama walks into the 'Bar': Efficient Supervised Fine-Tuning for Legal Reasoning in the Multi-state Bar Exam
by: Fernandes, Rean, et al.
Published: (2025) -
Hierarchical Transformers are Efficient Meta-Reinforcement Learners
by: Shala, Gresa, et al.
Published: (2024) -
On the Generalization of Data-Assisted Control in port-Hamiltonian Systems (DAC-pH)
by: Eslami, Mostafa, et al.
Published: (2025) -
Dreaming of Many Worlds: Learning Contextual World Models Aids Zero-Shot Generalization
by: Prasanna, Sai, et al.
Published: (2024)