Improve the performance of your generative AI applications with Prompt Optimization on Amazon Bedrock
Rapid engineering refers to the practice of writing instructions to obtain desired responses from basic models (FM). You may have ...
Tag: Optimization
Private convex stochastic optimization with heavy tails: quasi-optimization from simple reductions
We study the differentially private convex stochastic optimization (DP-SCO) problem with heavy-tailed gradients, where we assume a kth<annotation encoding="application/x-tex">k^{\text{th}}kth-momentum limit ...
Faster Algorithms for User-Level Private Stochastic Convex Optimization
We study private stochastic convex optimization (SCO) under user-level differential privacy (DP) constraints. In this scenario, there is north<annotation encoding="application/x-tex">northnorth ...
Meet Aioli: A Unified Optimization Framework for Language Model Data Blending
In recent years, training large language models has faced a crucial challenge: determining the optimal combination of data. Models like ...
YouTube SEO Optimization with ChatGPT
Since ChatGPT was launched, it has significantly changed the way people communicate, create content, and optimize their work for search ...
Adaptive Data Optimization (ADO): A new algorithm for dynamic data distribution in machine learning, reducing complexity and improving model accuracy
Machine learning, particularly the training of large basic models, relies heavily on the diversity and quality of data. These models, ...
AFlow: A New AI Framework for Automated Workflow Optimization
The challenge lies in generating effective agent workflows for large language models (LLM). Despite their notable capabilities across multiple tasks, ...
Building Five Machine Learning Models: From Simplicity to Optimization
Build, compare and optimize models.Model selectionNow we move on to the second part of our project in Selection of machine ...
On the limited generalization capacity of the implicit reward model induced by direct preference optimization.
Reinforcement learning from human feedback (RLHF) is an effective approach to align language models with human preferences. Fundamental to RLHF ...
Understanding SciPy Library in Python
Introduction Suppose you are a scientist or an engineer solving numerous problems – ordinary differential equations, extremal problems, or Fourier ...
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