138 citations
- Amazon (United States)US6 papers
- University of BristolGB3 papers
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- Universidad Politécnica de MadridES2 papers
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- Aalto UniversityFI1 paper
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- Amsterdam University of the ArtsNL1 paper
- Bilkent UniversityTR1 paper
7 papers · 1 filter
Low-count Time Series Anomaly Detection
Philipp Renz, Kurt Cutajar, Niall Twomey +2
Low-count time series describe sparse or intermittent events, which are prevalent in large-scale online platforms that capture and monitor diverse data types. Several distinct chal…
Learning Action Embeddings for Off-Policy Evaluation
Matej Cief, Jacek Golebiowski, Philipp Schmidt +2
Off-policy evaluation (OPE) methods allow us to compute the expected reward of a policy by using the logged data collected by a different policy. OPE is a viable alternative to run…
Inference and Learning for Generative Capsule Models
Alfredo Nazabal, Nikolaos Tsagkas, Christopher K. I. Williams
Capsule networks (see e.g. Hinton et al., 2018) aim to encode knowledge of and reason about the relationship between an object and its parts. In this paper we specify a generative…
Exposing Previously Undetectable Faults in Deep Neural Networks
Isaac Dunn, Hadrien Pouget, Daniel Kroening +1
Existing methods for testing DNNs solve the oracle problem by constraining the raw features (e.g. image pixel values) to be within a small distance of a dataset example for which t…
Using VAEs and Normalizing Flows for One-shot Text-To-Speech Synthesis of Expressive Speech
Vatsal Aggarwal, Marius Cotescu, Nishant Prateek +2
We propose a Text-to-Speech method to create an unseen expressive style using one utterance of expressive speech of around one second. Specifically, we enhance the disentanglement…
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising
Borja Balle, Yu-Xiang Wang
The Gaussian mechanism is an essential building block used in multitude of differentially private data analysis algorithms. In this paper we revisit the Gaussian mechanism and show…