Graph Representations and Algorithms in Biomedicine

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.

Understanding the diffusion patterns of sequences of interdependent events is a central question for a variety of disciplines. Temporal point processes are a class of elegant and powerful models of such sequences; these processes have become popular across ...

Semidefinite programming (SDP) is a powerful framework from convex optimization that has striking potential for data science applications. This paper develops a provably correct algorithm for solving large SDP problems by economizing on both the storage an ...

We study the computations that Bayesian agents undertake when exchanging opinions over a network. The agents act repeatedly on their private information and take myopic actions that maximize their expected utility according to a fully rational posterior be ...

In distributed optimization and machine learning, multiple nodes coordinate to solve large problems. To do this, the nodes need to compress important algorithm information to bits so that it can be communicated over a digital channel. The communication tim ...

An integer program (IP) is a problem of the form

\min \{f(x) : \, Ax = b, \ l \leq x \leq u, \ x \in \Z^n\}

, where

A \in \Z^{m \times n}

b \in \Z^m

l,u \in \Z^n

, and

f: \Z^n \rightarrow \Z

is a separable convex objective function. The problem o ...

We solve a rich routing problem inspired from practice, in which a heterogeneous fixed fleet is used for collecting recyclable waste from large containers over a finite planning horizon. Each container is equipped with a sensor that communicates its level ...

The slowing down of Moore's law and the emergence of new technologies puts an increasing pressure on the field of EDA. There is a constant need to improve optimization algorithms. However, finding and implementing such algorithms is a difficult task, espec ...

We present a methodology for identifying patients who have experienced Paroxysmal Atrial Fibrillation (PAF) among a given subject population. Our work is intended as an initial step towards the design of an unobtrusive portable system for concurrent detect ...

This paper considers the issues of efficiency and autonomy that are required to make reinforcement learning suitable for real-life control tasks. A real-time reinforcement learning algorithm is presented that repeatedly adjusts the control policy with the ...

We describe a non-blocking concurrent hash trie based on shared-memory single-word compare-and-swap instructions. The hash trie supports standard mutable lock-free operations such as insertion, removal, lookup and their conditional variants. To ensure spac ...

Comparing two or more phylogenetic trees is a fundamental task in computational biology. The simplest outcome of such a comparison is a pairwise measure of similarity, dissimilarity, or distance. A large number of such measures have been proposed, but so t ...

Estimating the parameters of a dynamical system based on measurements is an important task in industrial and scientific practice. Since a model's quality is directly linked to its parameter values, obtaining globally rather than locally optimal values is e ...

We consider the class of piecewise affine optimal state feedback control laws applied to discrete-time piecewise affine systems, motivated by recent work on the computation of closed-form MPC controllers. The storage demand and complexity of these optimal ...

Graph Representations and Algorithms in Biomedicine

Chat with Graph Search

Learning Self-Exciting Temporal Point Processes Under Noisy Observations

Scalable Semidefinite Programming

Bayesian Decision Making in Groups is Hard

On Maintaining Linear Convergence of Distributed Learning and Optimization Under Limited Communication

New Results in Integer and Lattice Programming

Waste collection inventory routing with non-stationary stochastic demands

Deep Learning for Logic Optimization Algorithms

Risk Assessment of Atrial Fibrillation: a Failure Prediction Approach

Autonomous reinforcement learning with experience replay

Concurrent Tries with Efficient Non-Blocking Snapshots

A metric for phylogenetic trees based on matching

Incremental Global Parameter Estimation in Dynamical Systems

Controller complexity reduction for piecewise affine systems through safe region elimination