Blar i Fakultet for informasjonsteknologi og elektroteknikk (IE) på tidsskrift "Proceedings of Machine Learning Research (PMLR)"

Viser treff 1-6 av 6

    • Differential privacy for symmetric log-concave mechanisms 

      Vinterbo, Staal (Peer reviewed; Journal article, 2022)
      Adding random noise to database query results is an important tool for achieving privacy. A challenge is to minimize this noise while still meeting privacy requirements. Recently, a sufficient and necessary condition for ...

    • ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results 

      Myers, Adele; Utpala, Saiteja; Talbar, Shubham; Sanborn, Sophia; Shewmake, Christian; Donnat, Claire; Mathe, Johan; Lupo, Umberto; Sonthalia, Rishi; Cui, Xinyue; Szwagier, Tom; Pignet, Arthur; Bergsson, Andri; Hauberg, Søren; Nielsen, Dmitriy; Sommer, Stefan; Klindt, David; Hermansen, Erik; Vaupel, Melvin; Dunn, Benjamin Adric; Xiong, Jeffrey; Aharony, Noga; Noga, Aharony; Pe’er, Itsik; Ambellan, Felix; Hanik, Martin; Nava-Yazdani, Esfandiar; von Tycowicz, Christoph; Miolane, Nina (Peer reviewed; Journal article, 2022)
      This paper presents the computational challenge on differential geometry and topology that was hosted within the ICLR 2022 workshop “Geometric and Topo- logical Representation Learning”. The competition asked participants ...

    • Linear Antisymmetric Recurrent Neural Networks 

      Moe, Signe; Remonato, Filippo; Grøtli, Esten Ingar; Gravdahl, Jan Tommy (Peer reviewed; Journal article, 2020)
      Recurrent Neural Networks (RNNs) have a form of memory where the output from a node at one timestep is fed back as input the next timestep in addition to data from the previous layer. This makes them highly suitable for ...

    • Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles 

      Saleh Salem, Tárik; Langseth, Helge; Ramampiaro, Heri (Peer reviewed; Journal article, 2020)
      Prediction intervals are a machine- and human-interpretable way to represent predictive uncertainty in a regression analysis. In this paper, we present a method for generating prediction intervals along with point estimates ...

    • A Reparameterization of Mixtures of Truncated Basis Functions and its Applications 

      Salmeron, Antonio; Langseth, Helge; Masegosa, Andres; Nielsen, Thomas D. (Peer reviewed; Journal article, 2022)
      Mixtures of truncated basis functions (MoTBFs) are a popular tool within the context of hybrid Bayesian networks, mainly because they are compatible with e_cient probabilistic inference schemes. However, their standard ...

    • Vector Quantized Time Series Generation with a Bidirectional Prior Model 

      Lee, Daesoo; Malacarne, Sara; Aune, Erlend (Journal article; Peer reviewed, 2023)
      Time series generation (TSG) studies have mainly focused on the use of Generative Adversarial Networks (GANs) combined with recurrent neural network (RNN) variants. However, the fundamental limitations and challenges of ...