Events in July–August 2017
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June 29, 2017(1 event)
A stochastic approach for optimizing green energy consumption in distributed clouds by Fanny Dufossé (Inria)A stochastic approach for optimizing green energy consumption in distributed clouds by Fanny Dufossé (Inria) – A stochastic approach for optimizing green energy consumption in distributed clouds The energy drawn by Cloud data centers is reaching worrying levels, thus inciting providers to install on-site green energy producers, such as photovoltaic panels. Considering distributed Clouds, workload managers need to geographically allocate virtual machines according to the green production in order not to waste energy. In this paper, we propose SAGITTA: a Stochastic Approach for Green consumption In disTributed daTA centers. We show that compared to the optimal solution, SAGITTA consumes 4% more brown energy, and wastes only 3.14% of the available green energy, while a traditional round-robin solution consumes 14.4% more energy overall than optimum, and wastes 28.83% of the available green energy. Bâtiment IMAG (442) |
June 30, 2017
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July 6, 2017(2 events)
Séminaire Josu Doncel : Under-Approximation Computation Through Optimal ControlSéminaire Josu Doncel : Under-Approximation Computation Through Optimal Control – Title: Under-Approximation Computation Through Optimal Control Abstract: Under-approximation provides a subset of the reachable set of an uncertain dynamical system which can then be used to formally falsify properties of quantitative models. Using Pontryagin’s principle, our approach computes an under-approximation for a linear combination of state variables of nonlinear ordinary differential equations and time-varying uncertainties. By a numerical comparison against state-of-the-art tools Flow^∗ and CORA, we show that our methodology provides tight under-approximations in benchmarks, and that it can scale to models that are out of reach with these over-approximation techniques. Bâtiment IMAG (442) I/O performance for HPC: finding the right access pattern and avoiding interference by Francieli Zanon-BoitoI/O performance for HPC: finding the right access pattern and avoiding interference by Francieli Zanon-Boito – Title: Abstract: Bâtiment IMAG (442) |
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- April 3, 2024 @ Bâtiment IMAG (442) -- [Seminar] Victor Boone
Who: Victor Boone
When: Wednesday, April 3, 14:00-15:00
Where: 447
What: Learning MDPs with Extended Bellman Operators
More: Efficiently learning Markov Decision Processes (MDPs) is difficult. When facing an unknown environment, where is the adequate limit between repeating actions that have shown their efficiency in the past (exploitation of your knowledge) and testing alternatives that may actually be better than what you currently believe (exploration of the environment)? To bypass this dilemma, a well-known solution is the "optimism-in-face-of-uncertainty" principle: Think of the score of an action as being the largest that is statistically plausible.
The exploration-exploitation dilemma then becomes the problem of tuning optimism. In this talk, I will explain how optimism in MDPs can be all rephrased using a single operator, embedding all the uncertainty in your environment within a single MDP. This is a story about "extended Bellman operators" and "extended MDPs", and about how one can achieve minimax optimal regret using this machinery.
- April 11, 2024 @ Bâtiment IMAG (442) -- [Seminar] Charles Arnal
Who: Charles Arnal
When: Thursday, April 11, 14:00-15:00
Where: 442
What: Mode Estimation with Partial Feedback
More: The combination of lightly supervised pre-training and online fine-tuning has played a key role in recent AI developments. These new learning pipelines call for new theoretical frameworks. In this paper, we formalize core aspects of weakly supervised and active learning with a simple problem: the estimation of the mode of a distribution using partial feedback. We show how entropy coding allows for optimal information acquisition from partial feedback, develop coarse sufficient statistics for mode identification, and adapt bandit algorithms to our new setting. Finally, we combine those contributions into a statistically and computationally efficient solution to our problem.
- April 30, 2024 @ Bâtiment IMAG (442) -- Seminar Rémi Castera
Correlation of Rankings in Matching Markets
