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Found 3 papers, 1 papers with code
Hierarchical Classification of Financial Transactions Through Context-Fusion of Transformer-based Embeddings and Taxonomy-aware Attention Layer
This work proposes the Two-headed DragoNet, a Transformer-based model for hierarchical multi-label classification of financial transactions.
Exploiting Low-Rank Structure in Semidefinite Programming by Approximate Operator Splitting
The main contribution of this work is to achieve a substantial speedup by effectively adjusting the proposed algorithm in order to exploit the low-rank property inherent to several semidefinite programming problems.
Optimization and Control
BooST: Boosting Smooth Trees for Partial Effect Estimation in Nonlinear Regressions
In this paper, we introduce a new machine learning (ML) model for nonlinear regression called the Boosted Smooth Transition Regression Trees (BooST), which is a combination of boosting algorithms with smooth transition regression trees.
