#metaheuristicalgorithm search results
This is more than a statistical practice, since a resulting optimal method, MoDaH, reaches SOTA performances when benchmarked against widely adopted heuristics over a diverse collection of datasets, e.g., Harmony, Seurat V5, and LIGER. (3/5)
Ineffectiveness for Search and Undecidability of PCSP Meta-Problems. arxiv.org/abs/2504.04639
My engine solves this by incorporating a lineage heuristic. Tracking all vectors that produces a non Opaque solution to understanding a neural network. colab.research.google.com/drive/1IyDOr0r…
Formulating it as a convex optimization problem lets us leverage well-established toolbox to actually solve this problem of finding the optimal optimizer for any given task. This is exactly what we did. We can derive many popular optimizers (#SGD, #Adam, #Muon, etc.) as…
Ah, got it—clarifying the infinite reasoning on the meta-approach. Loop starts: Emergent criteria (applicability, resilience, productivity) derive from frameworks, but scoring them requires assuming their validity—circularity. Iterate: Refine criteria via feedback? But…
This is the only algorithm you need. Wait for your setup. Execute without hesitation. Wait again. Anything else is noise that costs you money. Master this simple loop. Good night 😴
🔥 Meta reveals a massive inefficiency in AI’s reasoning process and gives a solution. Large language models keep redoing the same work inside long chains of thought. For example, when adding fractions with different denominators, the model often re explains finding a common…
🔥 Read our Highly Cited Paper 📚 #RealTimeOptimization of Heliostat Field Aiming Strategy via an Improved #SwarmIntelligence Algorithm 🔗 mdpi.com/2076-3417/14/1… 👨🔬 Yi’an Wang, Zhe Wu and Dong Ni 🏫 @ZJU_China / @NUSingapore #metaheuristicalgorithm #solarpowertower
Beautiful Paper Meta-Chain-of-Thought helps LLMs learn to search, backtrack and verify. Meta Chain-of-Thought extends traditional Chain-of-Thought prompting by modeling the underlying search and verification process that humans use when solving complex problems. ----- 🤔…
We invite you to submit your excellent paper to #specialissue "Artificial Intelligence for More Efficient Renewable Energy Systems". mdpi.com/journal/algori… The #deadline has been extended to 30 June 2025. #metaheuristicalgorithm #renewableenergysystems #callforpapers
Energy Efficiency Optimisation of Joint Computational Task Offloading and Resource Allocation Using Particle Swarm Optimisation Approach in Vehicular Edge Networks mdpi.com/1424-8220/24/1… #energyefficiency; #metaheuristicalgorithm; #vehicularedgecomputing
Iterative Reasoning Preference Optimization abs: arxiv.org/abs/2404.19733 New paper from Meta applying iterative preference optimization to improve reasoning: generate chain-of-thought candidates with LLM, construct preference pairs based on if answer is correct or not, train…
Meta presents Efficient Tool Use with Chain-of-Abstraction Reasoning huggingface.co/papers/2401.17… In mathematical reasoning and Wiki QA domains, we show that our method consistently outperforms previous chain-of-thought and tool-augmented baselines on both in-distribution and…
Facebook-Meta Hacker Cup - I Qualified for round 3. Total 28 folks qualified from India. Problem Intuitions - Problem A1: Ready, Go (Part 1) - Consider this as a graph. Make components of nodes having White stones. Then create edges between these components and empty places. Now…
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models paper page: huggingface.co/papers/2309.12… Large language models (LLMs) have pushed the limits of natural language understanding and exhibited excellent problem-solving ability. Despite the great success,…
LLMs as Optimizers This is a really neat idea. This new paper from Google DeepMind proposes an approach where the optimization problem is described in natural language. An LLM is then instructed to iteratively generate new solutions based on the defined problem and previously…
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