(04.2020) Program committee (PC) member for 1st Workshop on Artificial Intelligence for Anomalies and Novelties (AI4AN 2020)
(03.2020) KDD program committee (PC) member, anomaly detection
(02.2020) Our “Deep semi-supervised anomaly detection paper” was accepted at ICLR 2020!
(31.01.2020) Winner announcement: We have 3 winner of the 123ai.de mechanical mascot! Congrats
(13.12.2019) First giveaway announcement!
(11.12.2019) First weekly newsletter!
(02.12.2019-06.12.2019) I organized the corporate training week on Bayesian Learning for Petrobras in Rio de Janeiro
(09.09.2019) 123AI.de funding starts
(31.08.2019) Last day as a post doc at the machine learning group at the TU Berlin
(24.04.2019-08.05.2019) I organized a 2-week workshop “Introduction to Machine Learning” at Petrobras in Rio de Janeiro and delivered the lectures on Bayesian learning and variational inference
(01.03.2019) Paper on “Deep Semi-Supervised Anomaly Detection” is now available in arXiv.
(22.12.2018) Our paper on “Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs” has been accepted at AISTATS 2019
(26.11.2018-30.11.2018) I gave a 4-day workshop on “Introduction to Anomaly Detection” at Petrobras in Rio de Janeiro
(29.06.2018) We have a new arXiv paper out “Unsupervised Detection and Explanation of Latent-class Contextual Anomalies“
(07.03.2018) Our ICML paper on “Deep one-class classification” is out in the wild
(15.12.2017) I jotted down some thoughts about explanation and interpretation of machine learning models. The main idea was to categorize approaches into a meaningful taxonomy. The blog post can be found here
(01.10.2017) Our paper “Ensembles of Lasso Screening Rules” (Seunghak Lee, Nico Görnitz, Eric P. Xing, David Heckerman, and Christoph Lippert) is finally accepted for publication in TPAMI!
(01.08.2017) Our paper “Support vector data descriptions and k-means clustering: one class?,” is accepted for publication in IEEE TNNLS
(02.06.2017) Our paper “Minimizing Trust Leaks for Robust Sybil Detection” is accepted for publication at ICML
(20.05.2017) Our paper “Transductive Regression for Data with Latent Dependency Structure” is accepted for publication in IEEE TNNLS
(19.05.2017) …and parental leave starts!
(03.05.2017) Our paper “Porosity Estimation by Semi-supervised Learning with Sparsely Available Labeled Samples” is accepted for publication in Computers and Geosciences
(27.03.2017) Our paper “ML2Motif—Reliable extraction of discriminative sequence motifs from learning machines” is accepted for publication in PLoS one!
(24.11.2016) Our paper “Feature Importance Measure for Non-linear Learning Algorithms” won the best paper award at the Interpretable ML for Complex Systems (NIPS Workshop)!
(19.06.2016) We setup an online tool for collecting your questions to the panel for the ICML anomaly detection workshop. You can also up-vote questions. The list can be accessed here
(06.06.2016) Registration for ICML is back online (Tickets for tutorials, conference, and workshops still available)
(03.06.2016) Only 3 weeks to go for our workshop (unfortunately workshop tickets for the ICML 2016 are sold-out now)