Youtubed activities
Nov 2024
29
Nov
The functools python module
First, we recall several concepts (lambda functions, callbacks, callables, functors, decorators) needed for the rest of the presentation. Second, we present the "functools" module, which [...]
27
Nov
Knowledge Graphs Construction using Small Language Models
This talk demonstrates how to efficiently Knowledge Graphs Construction using Small Language Models like Llama-3.2-3B, showing practical techniques for extracting structured knowledge from JSON and [...]
22
Nov
Lagrangian multipliers, normal cones and KKT optimality conditions
Lagrange multipliers are a go-to tool for anyone who’s worked in optimization. In this talk we will explore the renowned Karush-Kuhn-Tucker optimality conditions starting from [...]
15
Nov
Optimizing Energy Consumption and Performance in Modern Cloud Systems
In the modern era of data-driven innovation, the challenge of optimizing energy consumption without sacrificing performance in modern cloud system networks has become increasingly important. [...]
08
Nov
uv: an extremely fast Python package installer and resolver & marimo notebooks: rethinking the notebook to create reproducible notebooks
In this session, we will talk about uv, an extremely fast Python package and project manager designed as a single tool to replace pip, pip-tools, [...]
06
Nov
The Squared Kemeny Rule for Averaging Rankings
For the problem of aggregating several rankings into one ranking, Kemeny (1959) proposed two methods: the median rule which selects the ranking with the smallest [...]
Oct 2024
30
Oct
Optimal time partitioning in V2V ISAC Systems
Platooning-based vehicle-to-vehicle (V2V) integrated sensing and communication (ISAC) frameworks have emerged as an attractive strategy in recent years. In this work, we present an optimal [...]
25
Oct
Hierarchical Community Detection in Hierarchical Stochastic Block Models
In this session of our reading group, I will discuss community detection in hierarchical clustering of networks, based on the paper "When Does Bottom-up Beat Top-down [...]
18
Oct
Understanding Reinforcement Learning error in image-based environments
In many Reinforcement Learning (RL) environments the state is represented by an image. In such cases, if the RL doesn’t work well, is the problem [...]
18
Oct
Decentralized Federated Policy Gradient with Byzantine Fault-Tolerance and Provably Fast Convergence
In Federated Reinforcement Learning (FRL), agents aim to collaboratively learn a common task, while each agent is acting in its local environment without exchanging raw [...]