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Found 5 papers, 1 papers with code
Differentiable Optimization of Generalized Nondecomposable Functions using Linear Programs
We propose a framework which makes it feasible to directly train deep neural networks with respect to popular families of task-specific non-decomposable per- formance measures such as AUC, multi-class AUC, F -measure and others, as well as models such as non-negative matrix factorization.
A Biresolution Spectral Framework for Product Quantization
In this paper, we study the quantization problem in the setting where subspaces are orthogonal and show that this problem is intricately related to a specific type of spectral decomposition of the data.
Filter Flow Made Practical: Massively Parallel and Lock-Free
This paper is inspired by a relatively recent work of Seitz and Baker which introduced the so-called Filter Flow model.
An NMF Perspective on Binary Hashing
In this paper, we first derive an Augmented Lagrangian approach to optimize the standard binary Hashing objective (i. e., maintain fidelity with a given distance matrix).
Gaze-Enabled Egocentric Video Summarization via Constrained Submodular Maximization
Motivated by these applications, this paper focuses on the problem of egocentric video summarization.
