Automated Motion LoD with Rigid Constraints

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.

We develop new tools to study landscapes in nonconvex optimization. Given one optimization problem, we pair it with another by smoothly parametrizing the domain. This is either for practical purposes (e.g., to use smooth optimization algorithms with good g ...

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

Orthogonal group synchronization is the problem of estimating n elements Z(1),& mldr;,Z(n) from the rxr orthogonal group given some relative measurements R-ij approximate to Z(i)Z(j)(-1). The least-squares formulation is nonconvex. To avoid its local minim ...

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

A method for optimizing at least one of a geometry, an implantation procedure, and/or stimulation protocol of one or more electrodes for an electrical stimulation of a target structure in a nervous system of a living being by a computer device, the method ...

This paper develops a fast algorithm for computing the equilibrium assignment with the perturbed utility route choice (PURC) model. Without compromise, this allows the significant advantages of the PURC model to be used in large-scale applications. We form ...

In various robotics applications, the selection of function approximation methods greatly influences the feasibility and computational efficiency of algorithms. Tensor Networks (TNs), also referred to as tensor decomposition techniques, present a versatile ...

Robots outside of the fenced factories have to deal with continuously changing environment, this requires fast and flexible modes of control. Planning methods or complex learning models can find optimal paths in complex surroundings, but they are computati ...

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

Video DeepFakes are fake media created with Deep Learning (DL) that manipulate a person’s expression or identity. Most current DeepFake detection methods analyze each frame independently, ignoring inconsistencies and unnatural movements between frames. Som ...

Objective. A key challenge of virtual reality (VR) applications is to maintain a reliable human-avatar mapping. Users may lose the sense of controlling (sense of agency), owning (sense of body ownership), or being located (sense of self-location) inside th ...

Multiple tensor-times-matrix (Multi-TTM) is a key computation in algorithms for computing and operating with the Tucker tensor decomposition, which is frequently used in multidimensional data analysis. We establish communication lower bounds that determine ...

The growing popularity of virtual reality systems has led to a renewed interest in understanding the neurophysiological correlates of the illusion of self-motion (vection), a phenomenon that can be both intentionally induced or avoided in such systems, dep ...

Quantum support vector machines employ quantum circuits to define the kernel function. It has been shown that this approach offers a provable exponential speedup compared to any known classical algorithm for certain data sets. The training of such models c ...

We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

We report the detailed background for the discovery and development of the synthesis of homopropargylic azides by the azidoalkynylation of alkenes. Initially, a strategy involving SOMOphilic alkynes was adopted, but only resulted in a 29% yield of the desi ...

VR (Virtual Reality) is a real-time simulation that creates the subjective illusion of being in a virtual world. This thesis explores how integrating the user's body and fingers can be achieved and beneficial for the user to experience VR. At the advent of ...

Automated Motion LoD with Rigid Constraints

Chat with Graph Search

The effect of smooth parametrizations on nonconvex optimization landscapes

Scalable constrained optimization

BENIGN LANDSCAPES OF LOW-DIMENSIONAL RELAXATIONS FOR ORTHOGONAL SYNCHRONIZATION ON GENERAL GRAPHS

Mesh-based topology, shape and sizing optimization of ribbed plates

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

A method and system for optimizing design, implantation, and stimulation protocols of electrodes stimulating the nervous system

Perturbed Utility Stochastic Traffic Assignment

Robot Learning using Tensor Networks

Exact Obstacle Avoidance for Robots in Complex and Dynamic Environments Using Local Modulation

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

A ride time-oriented scheduling algorithm for dial-a-ride problems

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Customizing the human-avatar mapping based on EEG error related potentials during avatar-based interaction

COMMUNICATION LOWER BOUNDS AND OPTIMAL ALGORITHMS FOR MULTIPLE TENSOR-TIMES-MATRIX COMPUTATION

Modulation of Visually Induced Self-motion Illusions by α Transcranial Electric Stimulation over the Superior Parietal Cortex

The complexity of quantum support vector machines

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

SOMOphilic alkyne vs radical-polar crossover approaches: The full story of the azido-alkynylation of alkenes

From finger animation to full-body embodiment of avatars with different morphologies and proportions