According to our experimental findings, inaccurate cross-attention maps are at the root of this problem.

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.

Neural Information Processing Systems http://nips.cc/

On both synthetic and real data, we empirically show that our proposed algorithm is able to learn better CVaRoptimizedpolicies.

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

Stochastic Gradient Descent (SGD) has been the method of choice for learning large-scale non-convex models. While a general analysis of when SGD works has been elusive, there has been a lot of recent progress in understanding the convergence of Gradient Flow (GF) on the population loss, partly due to the simplicity thatacontinuous-time analysis buysus.