17 papers · ranked by Valyu relevance
Astha Saini, Petre Stoica, Prabhu Babu, Aakash Arora
| 1 | Introduction | 312 | | --- | --- | --- | | | 1.1 | MM Summary 313 | | | 1.2 | Need for MM4MM 314 | | | 1.3 | Organization 315 | | | 1.4 | Notation 316 | | 2 | | Max Formulation 318 | | | 2.1 | Conjugate Function 319 | | | 2.2 | Max Formulation for Certain Non-Convex Functions 320 | | | 2.3 | Illustrative Examples…
Paul Magron, Cédric Févotte
This paper tackles the problem of decomposing binary data using matrix factorization. We consider the family of mean-parametrized Bernoulli models, a class of generative models that are well suited for modeling binary data and enables interpretability of the factors. We factorize the Bernoulli parameter and consider an…
Le Thi Khanh Hien, Valentin Leplat, Nicolas Gillis
We propose a Block Majorization Minimization method with Extrapolation (BMMe) for solving a class of multiconvex optimization problems. The extrapolation parameters of BMMe are updated using a novel adaptive update rule. By showing that block majorization minimization can be reformulated as a block mirror descent…
Shota Takahashi, Mirai Tanaka, Shiro Ikeda
nonnegative matrix factorization with the Kullback--Leibler divergence Authors: ['Shota Takahashi' 'Mirai Tanaka' 'Shiro Ikeda'] Nonnegative matrix factorization (NMF) is a popular method in machine learning and signal processing to decompose a given nonnegative matrix into two nonnegative matrices. In this paper, to…
Mehrsa Pourya, Sebastian Neumayer, Michael Unser
We propose a regularization scheme for image reconstruction that leverages the power of deep learning while hinging on classic sparsity-promoting models. Many deep-learning-based models are hard to interpret and cumbersome to analyze theoretically. In contrast, our scheme is interpretable because it corresponds to the…
Jian Chen, Liping Tang, Xinmin Yang
Majorization-Minimization Perspective Authors: ['Jian Chen' 'Liping Tang' 'Xinmin Yang'] In this paper, we develop a unified framework and convergence analysis of descent methods for vector optimization problems (VOPs) from a majorization-minimization perspective. By choosing different surrogate functions, the generic…
Yuxue Chen, Shuisheng Zhou, Boris Ryabko
Possibilistic fuzzy c-means (PFCM) clustering is a kind of hybrid clustering method based on fuzzy c-means (FCM) and possibilistic c-means (PCM), which not only has the stability of FCM but also partly inherits the robustness of PCM. However, as an extension of FCM on the objective function, PFCM tends to find a…
Rui Liang, Hui Li, Yingli Dong, Guodong Xue + 2 more
'Luca Barletta'] The practical implementation of massive multi-user multi-input-multi-output (MU-MIMO) downlink communication systems power amplifiers that are energy efficient; otherwise, the power consumption of the base station (BS) will be prohibitive. Constant envelope (CE) precoding is gaining increasing interest…
Alfonso Landeros, Oscar Hernan Madrid Padilla, Hua Zhou, Kenneth Lange
'Kenneth Lange'] The current paper studies the problem of minimizing a loss f(x) subject to constraints of the form Dx ∈ S, where S is a closed set, convex or not, and D is a matrix that fuses parameters. Fusion constraints can capture smoothness, sparsity, or more general constraint patterns. To tackle this generic…
Nathanaël Perraudin, Adrien Teutrie, C. Hébert, Guillaume Obozinski
Factorization Authors: ['Nathanaël Perraudin' 'Adrien Teutrie' 'C. Hébert' 'Guillaume Obozinski'] We consider the problem of regularized Poisson Non-negative Matrix Factorization (NMF) problem, encompassing various regularization terms such as Lipschitz and relatively smooth functions, alongside linear constraints.…
Alfonso Landeros, Seyoon Ko, Jack Z. Chang, Tong Tong Wu + 1 more
'Kenneth Lange'] Modern biomedical datasets are often high-dimensional at multiple levels of biological organization. Practitioners must therefore grapple with data to estimate sparse or low-rank structures so as to adhere to the principle of parsimony. Further complicating matters is the presence of groups in data…
Zhihao Liu, Minghao Chen, Jingmin Hu, Yonghong Wang + 1 more
Cells choose between alternative pathways in metabolic networks under diverse environmental conditions, but the principles governing the choice are insufficiently understood, especially in response to dynamically changing conditions. Here we observed that a lactic acid bacterium Bacillus coagulans displayed homolactic…
Ove Øyås, Axel Theorell, Jörg Stelling
Many interactions in microbial consortia or tissues of multicellular organisms rely on networks of metabolite exchanges. To predict community function and composition beyond statistical correlations, one can use genome-scale metabolic models. However, comprehensive model analysis via metabolic pathways is a major…
AKHIL SHAJAN, Madushanka Manathunga, Andreas Goetz, Kenneth Merz
Based on a series of energy minimizations with starting structures obtained from the Baker test set of 30 organic molecules, a comparison is made between various open-source geometry optimization codes that are interfaced with the open-source QUantum Interaction Computational Kernel (QUICK) program for gradient and…
Max Ward, Eliot Courtney, Elena Rivas
An RNA design algorithm takes a target RNA structure and finds a sequence that folds into that structure. This is fundamentally important for engineering therapeutics using RNA. Computational RNA design algorithms are guided by fitness functions, but not much research has been done on the merits of these functions. We…
Peter L. Bartlett, Chris Junchi Li, Jingfeng Wu, Bin Yu
In the field of optimization, developing accelerated methods for solving minimax and fixed-point problems remains a fundamental challenge. This paper presents a novel family of dual accelerated algorithms that achieve optimal convergence rates for both minimax and fixed-point problems. By exploring new anchoring…
Akhil Shajan, Madushanka Manathunga, Andreas Goetz, Kenneth Merz
Based on a series of energy minimizations with starting structures obtained from the Baker test set of 30 organic molecules, a comparison is made between various open- source geometry optimization codes that are interfaced with the open-source QUantum Interaction Computational Kernel (QUICK) program for gradient and…