local optima
Local optima refer to points in the loss landscape of an optimization problem that represent the best solution within a limited region but are not the best overall (global minima). Deep learning algorithms often get trapped in local optima.
- Evolutionary Multi-View Classification via Eliminating Individual Fitness Bias
- FP64 is All You Need: Rethinking Failure Modes in Physics-Informed Neural Networks
- Fractional Langevin Dynamics for Combinatorial Optimization via Polynomial-Time Escape
- Memory-Augmented Potential Field Theory: A Framework for Adaptive Control in Non-Convex Domains
- Multimodal LiDAR-Camera Novel View Synthesis with Unified Pose-free Neural Fields
- No Loss, No Gain: Gated Refinement and Adaptive Compression for Prompt Optimization
- Optimizing the Unknown: Black Box Bayesian Optimization with Energy-Based Model and Reinforcement Learning
- ReDit: Reward Dithering for Improved LLM Policy Optimization
- Rising from Ashes: Generalized Federated Learning via Dynamic Parameter Reset
- Sculpting Features from Noise: Reward-Guided Hierarchical Diffusion for Task-Optimal Feature Transformation
- The Complexity of Finding Local Optima in Contrastive Learning
- The Lighthouse of Language: Enhancing LLM Agents via Critique-Guided Improvement