Publications related to Structural Screening and Design of Platinum Nanosamples for Oxygen Reduction

Robust Data-Driven Controller Design with Finite Frequency Samples

Alireza Karimi, Philippe Louis Schuchert

Modern control synthesis methods rely on accurate models to derive a performant controller. Obtaining a good model is often a costly step, and has led to a renewed interest in data-driven synthesis methods. Frequency-response-based synthesis methods have b ...

2024

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Soumaya Elkantassi

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. Th ...

EPFL2023

Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance

Gabriel Okasa

Estimation of causal effects using machine learning methods has become an active research field in econometrics. In this paper, we study the finite sample performance of meta-learners for estimation of heterogeneous treatment effects under the usage of sam ...

2022

Sampling-Based AQP in Modern Analytical Engines

Anastasia Ailamaki, Viktor Sanca

As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often consid ...

ACM2022

Planning for a Changing Climate without Accurate Predictions

Parag Rastogi, Mohammad Emtiyaz Khan

Simulation is an informative tool to plan the design and renovation of engineering systems, but its use requires accurate inputs from the users. Inputs such as the unknown future operating conditions might be expected in a system’s lifetime, e.g., the futu ...

Taylor & Francis Group2021

Sequential catalysis enables enhanced C-C coupling towards multi-carbon alkenes and alcohols in carbon dioxide reduction: a study on bifunctional Cu/Au electrocatalysts

Michael Graetzel, Shaik Mohammed Zakeeruddin, Jing Gao, Dan Ren

Electrochemical reduction of carbon dioxide (CO2) to multi-carbon products such as ethylene, ethanol and n-propanol offers a promising path for utilization of excessive CO2 and energy storage. Oxide-derived Cu electrodes are among the best electrocatalysts ...

ROYAL SOC CHEMISTRY2019

Retroactive Packet Sampling for Traffic Receipts

Pavlos Nikolopoulos, Adrian Perrig, Christos Pappas

Is it possible to design a packet-sampling algorithm that prevents the network node that performs the sampling from treating the sampled packets preferentially? We study this problem in the context of designing a "network transparency" system. In this syst ...

ACM2019

A Learning-Based Framework for Quantized Compressed Sensing

Volkan Cevher, Rabeeh Karimi Mahabadi, Junhong Lin

Sparse recovery from undersampled random quan- tization measurements is a recent active research topic. Previous work asserts that stable recovery can be guaranteed via the basis pursuit dequantizer (BPDQ) if the measurements number is large enough, consid ...

2019

Safe Adaptive Importance Sampling

Martin Jaggi, Sebastian Urban Stich, Anant Raj

Importance sampling has become an indispensable strategy to speed up optimization algorithms for large-scale applications. Improved adaptive variants - using importance values defined by the complete gradient information which changes during optimization - ...

2017

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function

u

in multivariate polynomial spaces

P_\Lambda:=span\{y\mapsto y^\nu \,: \, \nu\in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma:=[-1,1]^d

, based on the s ...

2017

Structural Screening and Design of Platinum Nanosamples for Oxygen Reduction

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Robust Data-Driven Controller Design with Finite Frequency Samples

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance

Sampling-Based AQP in Modern Analytical Engines

Planning for a Changing Climate without Accurate Predictions

Sequential catalysis enables enhanced C-C coupling towards multi-carbon alkenes and alcohols in carbon dioxide reduction: a study on bifunctional Cu/Au electrocatalysts

Retroactive Packet Sampling for Traffic Receipts

A Learning-Based Framework for Quantized Compressed Sensing

Safe Adaptive Importance Sampling

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Sampling-Based AQP in Modern Analytical Engines

Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Planning for a Changing Climate without Accurate Predictions

Retroactive Packet Sampling for Traffic Receipts

A Learning-Based Framework for Quantized Compressed Sensing

Safe Adaptive Importance Sampling

Robust Data-Driven Controller Design with Finite Frequency Samples

Sequential catalysis enables enhanced C-C coupling towards multi-carbon alkenes and alcohols in carbon dioxide reduction: a study on bifunctional Cu/Au electrocatalysts