253 citations
- Technicolor (Germany)DE18 papers
- Technicolor (France)FR11 papers
- Stanford UniversityUS7 papers
- Adobe Systems (United States)US6 papers
- Massachusetts Institute of TechnologyUS5 papers
- Rutgers, The State University of New JerseyUS4 papers
- University of MichiganUS4 papers
- Max Planck Institute for InformaticsDE3 papers
- University of AlbertaCA3 papers
- University of Wisconsin–MadisonUS3 papers
- Yahoo (United States)US3 papers
- Centre Inria de l'Université de LilleFR2 papers
41 papers
Spectral bandits for smooth graph functions with applications in recommender systems
Tomáš Kocák, Michal Valko, Rémi Munos +2
Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this paper, we study a bandit problem where the payoffs of arms are smooth on a graph…
Learning from a single labeled face and a stream of unlabeled data
Branislav Kveton, Michal Valko
Face recognition from a single image per person is a challenging problem because the training sample is extremely small. We consider a variation of this problem. In our problem, we…
Conditional anomaly detection with soft harmonic functions
Michal Valko, Branislav Kveton, Hamed Valizadegan +2
In this paper, we consider the problem of conditional anomaly detection that aims to identify data instances with an unusual response or a class label. We develop a new non-paramet…
StyleRig: Rigging StyleGAN for 3D Control over Portrait Images
Ayush Tewari, Mohamed Elgharib, Gaurav Bharaj +5
StyleGAN generates photorealistic portrait images of faces with eyes, teeth, hair and context (neck, shoulders, background), but lacks a rig-like control over semantic face paramet…
Matrix Completion in the Unit Hypercube via Structured Matrix Factorization
Emanuele Bugliarello, Swayambhoo Jain, Vineeth Rakesh
Several complex tasks that arise in organizations can be simplified by mapping them into a matrix completion problem. In this paper, we address a key challenge faced by our company…
Wide Compression: Tensor Ring Nets
Wenqi Wang, Yifan Sun, Brian Eriksson +2
Deep neural networks have demonstrated state-of-the-art performance in a variety of real-world applications. In order to obtain performance gains, these networks have grown larger…