Saved in:
| Main Authors: | Sabry, Mohammed, Khalifa, Amr M. A. |
|---|---|
| Format: | Preprint |
| Published: |
2019
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/1910.05983 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Suppressing Overestimation in Q-Learning through Adversarial Behaviors
by: Lee, HyeAnn, et al.
Published: (2023)
by: Lee, HyeAnn, et al.
Published: (2023)
Induction Signatures Are Not Enough: A Matched-Compute Study of Load-Bearing Structure in In-Context Learning
by: Sabry, Mohammed, et al.
Published: (2025)
by: Sabry, Mohammed, et al.
Published: (2025)
Assessing the Portability of Parameter Matrices Trained by Parameter-Efficient Finetuning Methods
by: Sabry, Mohammed, et al.
Published: (2024)
by: Sabry, Mohammed, et al.
Published: (2024)
Budgeted LoRA: Distillation as Structured Compute Allocation for Efficient Inference
by: Sabry, Mohammed, et al.
Published: (2026)
by: Sabry, Mohammed, et al.
Published: (2026)
QSIM: Mitigating Overestimation in Multi-Agent Reinforcement Learning via Action Similarity Weighted Q-Learning
by: Li, Yuanjun, et al.
Published: (2026)
by: Li, Yuanjun, et al.
Published: (2026)
On Variance Reduction in Learning Mean Flows
by: Lu, Juanwu, et al.
Published: (2026)
by: Lu, Juanwu, et al.
Published: (2026)
Semi-Variance Reduction for Fair Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024)
by: Malekmohammadi, Saber, et al.
Published: (2024)
Deep Time-Series Models Meet Volatility: Multi-Horizon Electricity Price Forecasting in the Australian National Electricity Market
by: Gani, Mohammed Osman, et al.
Published: (2026)
by: Gani, Mohammed Osman, et al.
Published: (2026)
Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning
by: Nauman, Michal, et al.
Published: (2024)
by: Nauman, Michal, et al.
Published: (2024)
Inexact Unlearning Needs More Careful Evaluations to Avoid a False Sense of Privacy
by: Hayes, Jamie, et al.
Published: (2024)
by: Hayes, Jamie, et al.
Published: (2024)
Conformal Risk Minimization with Variance Reduction
by: Noorani, Sima, et al.
Published: (2024)
by: Noorani, Sima, et al.
Published: (2024)
Adversarial Robustness Overestimation and Instability in TRADES
by: Li, Jonathan Weiping, et al.
Published: (2024)
by: Li, Jonathan Weiping, et al.
Published: (2024)
Variance Reduction Based Experience Replay for Policy Optimization
by: Zheng, Hua, et al.
Published: (2026)
by: Zheng, Hua, et al.
Published: (2026)
Non-Convex Optimization in Federated Learning via Variance Reduction and Adaptive Learning
by: Thakur, Dipanwita, et al.
Published: (2024)
by: Thakur, Dipanwita, et al.
Published: (2024)
SPRINT: Stochastic Performative Prediction With Variance Reduction
by: Xie, Tian, et al.
Published: (2025)
by: Xie, Tian, et al.
Published: (2025)
Variance Reduction via Resampling and Experience Replay
by: Han, Jiale, et al.
Published: (2025)
by: Han, Jiale, et al.
Published: (2025)
Personalized Collaborative Learning with Affinity-Based Variance Reduction
by: Zhang, Chenyu, et al.
Published: (2025)
by: Zhang, Chenyu, et al.
Published: (2025)
Variance Reduction for the Independent Metropolis Sampler
by: Liu, Siran, et al.
Published: (2024)
by: Liu, Siran, et al.
Published: (2024)
SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning
by: Sun, Jingruo, et al.
Published: (2025)
by: Sun, Jingruo, et al.
Published: (2025)
Issues with Value-Based Multi-objective Reinforcement Learning: Value Function Interference and Overestimation Sensitivity
by: Vamplew, Peter, et al.
Published: (2024)
by: Vamplew, Peter, et al.
Published: (2024)
Muon is Provably Faster with Momentum Variance Reduction
by: Qian, Xun, et al.
Published: (2025)
by: Qian, Xun, et al.
Published: (2025)
Stochastic Gradient Langevin Dynamics with Variance Reduction
by: Huang, Zhishen, et al.
Published: (2021)
by: Huang, Zhishen, et al.
Published: (2021)
Distributed Black-box Attack: Do Not Overestimate Black-box Attacks
by: Wu, Han, et al.
Published: (2022)
by: Wu, Han, et al.
Published: (2022)
Hybrid Deep Learning and Handcrafted Feature Fusion for Mammographic Breast Cancer Classification
by: Tschuchnig, Maximilian, et al.
Published: (2025)
by: Tschuchnig, Maximilian, et al.
Published: (2025)
Exploring Variance Reduction in Importance Sampling for Efficient DNN Training
by: Kutsuna, Takuro
Published: (2025)
by: Kutsuna, Takuro
Published: (2025)
Optimal-Point Variance Reduction For Bayesian Optimization With Regret Guarantee
by: Takeno, Shion
Published: (2026)
by: Takeno, Shion
Published: (2026)
Adaptive Multi-Fidelity Reinforcement Learning for Variance Reduction in Engineering Design Optimization
by: Agrawal, Akash, et al.
Published: (2025)
by: Agrawal, Akash, et al.
Published: (2025)
Deep Kernel Posterior Learning under Infinite Variance Prior Weights
by: Loría, Jorge, et al.
Published: (2024)
by: Loría, Jorge, et al.
Published: (2024)
Unifying On- and Off-Policy Variance Reduction Methods
by: Jeunen, Olivier
Published: (2026)
by: Jeunen, Olivier
Published: (2026)
Accelerating Byzantine-Robust Distributed Learning with Compressed Communication via Double Momentum and Variance Reduction
by: Li, Yanghao, et al.
Published: (2026)
by: Li, Yanghao, et al.
Published: (2026)
Sample Complexity of Variance-reduced Distributionally Robust Q-learning
by: Wang, Shengbo, et al.
Published: (2023)
by: Wang, Shengbo, et al.
Published: (2023)
Zeroth-Order Non-Log-Concave Sampling with Variance Reduction and Applications to Inverse Problems
by: Sahin, M. Berk, et al.
Published: (2026)
by: Sahin, M. Berk, et al.
Published: (2026)
Moderate Actor-Critic Methods: Controlling Overestimation Bias via Expectile Loss
by: Hwang, Ukjo, et al.
Published: (2025)
by: Hwang, Ukjo, et al.
Published: (2025)
The Benefits of Balance: From Information Projections to Variance Reduction
by: Liu, Lang, et al.
Published: (2024)
by: Liu, Lang, et al.
Published: (2024)
MARS-M: When Variance Reduction Meets Matrices
by: Liu, Yifeng, et al.
Published: (2025)
by: Liu, Yifeng, et al.
Published: (2025)
Domain Adapting Deep Reinforcement Learning for Real-world Speech Emotion Recognition
by: Rajapakshe, Thejan, et al.
Published: (2022)
by: Rajapakshe, Thejan, et al.
Published: (2022)
Projected Forward Gradient-Guided Frank-Wolfe Algorithm via Variance Reduction
by: Rostami, M., et al.
Published: (2024)
by: Rostami, M., et al.
Published: (2024)
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
by: Byambadalai, Undral, et al.
Published: (2024)
by: Byambadalai, Undral, et al.
Published: (2024)
Adversarial Attacks on Deep Learning-Based False Data Injection Detection in Differential Relays
by: Saber, Ahmad Mohammad, et al.
Published: (2025)
by: Saber, Ahmad Mohammad, et al.
Published: (2025)
Variance Reduction in Ratio Metrics for Efficient Online Experiments
by: Baweja, Shubham, et al.
Published: (2024)
by: Baweja, Shubham, et al.
Published: (2024)
Similar Items
-
Suppressing Overestimation in Q-Learning through Adversarial Behaviors
by: Lee, HyeAnn, et al.
Published: (2023) -
Induction Signatures Are Not Enough: A Matched-Compute Study of Load-Bearing Structure in In-Context Learning
by: Sabry, Mohammed, et al.
Published: (2025) -
Assessing the Portability of Parameter Matrices Trained by Parameter-Efficient Finetuning Methods
by: Sabry, Mohammed, et al.
Published: (2024) -
Budgeted LoRA: Distillation as Structured Compute Allocation for Efficient Inference
by: Sabry, Mohammed, et al.
Published: (2026) -
QSIM: Mitigating Overestimation in Multi-Agent Reinforcement Learning via Action Similarity Weighted Q-Learning
by: Li, Yuanjun, et al.
Published: (2026)