The low-resource label analysis and representation visualization further illustrate the effectiveness of our pre-training strategy.

This paper presents a text classification algorithm inspired by the notion of superposition of states in quantum physics.

Petitions demanding people get the chance to be released from ICE custody have overwhelmed courts throughout the US. The Immigration and Customs Enforcement (ICE) operation in Minnesota is pushing the United States court system to its breaking point. Since Operation Metro Surge began in December, federal immigration agents have arrested some 4,000 people, according to the Department of Homeland Security (DHS). The result is an avalanche of cases filed in the US district court in Minnesota on behalf of people challenging their imprisonment by federal immigration enforcement agents. According to WIRED's review of court records and official judicial statistics, attorneys filed nearly as many so-called habeas corpus petitions in Minnesota alone as were filed across the US during an entire year.

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Many zeroth-order (ZO) optimization algorithms have been developed to solve nonconvex minimax problems in machine learning and computer vision areas.

Meta learning aims to learn the inductive biases ( e .

Recently, federated multi-view clustering (FedMVC) has emerged to explore cluster structures in multi-view data distributed on multiple clients. Many existing approaches tend to assume that clients are isomorphic and all of them belong to either single-view clients or multi-view clients.

However,sincetheinitial large learning rate generally helps the optimizer to converge to flatter minima, we hypothesize that the winning tickets have relatively sharp minima, which is considered a disadvantage in terms of generalization ability.

The most extensive model described to date is the base model size encompasses 77.6M parameters