LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.
Abstract: Partial label learning (PLL) is an important problem that allows each training example to be labeled with a coarse candidate set with the ground-truth label included. However, in a more ...
Abstract: To improve the topology observability in power distribution networks (PDNs), a two-stage topology identification framework is proposed to recognize the mixed topologies in a large set of ...
In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...
Individual survival and evolutionary selection require biological organisms to maximize reward. Economic choice theories define the necessary and sufficient conditions, and neuronal signals of ...
In this article, our experts analyze the US-EU Summit’s outcomes and deliverables and what they mean for the future of US-EU relations. After a two year gap, US President Joe Biden, European ...
ChatGPT and other AIs could supercharge the influence of lobbyists—but only if we let them Nearly 90% of the multibillion-dollar federal lobbying apparatus in the United States serves corporate ...
Designing an incentive compatible auction that maximizes expected revenue is an intricate task. The single-item case was resolved in a seminal piece of work by Myerson in 1981. Even after 30–40 years ...
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