Related publications (5)

Analytical Engines With Context-Rich Processing: Towards Efficient Next-Generation Analytics

Anastasia Ailamaki, Viktor Sanca

As modern data pipelines continue to collect, produce, and store a variety of data formats, extracting and combining value from traditional and context-rich sources such as strings, text, video, audio, and logs becomes a manual process where such formats a ...
2023

Protecting Mobile Food Diaries from Getting too Personal

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Smartphone applications that use passive sensing to support human health and well-being primarily rely on: (a) generating low-dimensional representations from high-dimensional data streams; (b) making inferences regarding user behavior; and (c) using those ...
Association for Computing Machinery2020

Chaining Mutual Information and Tightening Generalization Bounds

Emmanuel Abbé

Bounding the generalization error of learning algorithms has a long history, which yet falls short in explaining various generalization successes including those of deep learning. Two important difficulties are (i) exploiting the dependencies between the h ...
NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Splitting the Smoothed Primal-Dual Gap: Optimal Alternating Direction Methods

Volkan Cevher, Quoc Tran Dinh

We develop rigorous alternating direction optimization methods for a prototype constrained convex optimization template, which has broad applications in computational sciences. We build upon our earlier work on the model-based gap reduction (MGR) technique ...
Tech. Report. LIONS-EPFL (2015)2015

Multiple phase derivative estimation using autoregressive modeling in holographic interferometry

Pramod Rastogi, Rishikesh Dilip Kulkarni

A novel technique is proposed for the direct and simultaneous estimation of multiple phase derivatives from a deformation modulated carrier fringe pattern in a multi-wave holographic interferometry set-up. The fringe intensity is represented as a spatially ...
Institute of Physics2015

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.