Search Results for author: Farnam Mansouri

Found 7 papers, 0 papers with code

A Labelled Sample Compression Scheme of Size at Most Quadratic in the VC Dimension

no code implementations24 Dec 2022 Farnam Mansouri, Sandra Zilles

This paper presents a construction of a proper and stable labelled sample compression scheme of size $O(\VCD^2)$ for any finite concept class, where $\VCD$ denotes the Vapnik-Chervonenkis Dimension.

Open-Ended Question Answering

Deep Reinforcement Learning for Online Control of Stochastic Partial Differential Equations

no code implementations NeurIPS Workshop DLDE 2021 Erfan Pirmorad, Faraz Khoshbakhtian, Farnam Mansouri, Amir-Massoud Farahmand

In many areas, such as the physical sciences, life sciences, and finance, control approaches are used to achieve a desired goal in complex dynamical systems governed by differential equations.

reinforcement-learning Reinforcement Learning (RL)

Preference-Based Batch and Sequential Teaching

no code implementations17 Oct 2020 Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla

We analyze several properties of the teaching complexity parameter $TD(\sigma)$ associated with different families of the preference functions, e. g., comparison to the VC dimension of the hypothesis class and additivity/sub-additivity of $TD(\sigma)$ over disjoint domains.

Understanding the Power and Limitations of Teaching with Imperfect Knowledge

no code implementations21 Mar 2020 Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla

Machine teaching studies the interaction between a teacher and a student/learner where the teacher selects training examples for the learner to learn a specific task.

Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models

no code implementations NeurIPS 2019 Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla

In our framework, each function $\sigma \in \Sigma$ induces a teacher-learner pair with teaching complexity as $\TD(\sigma)$.

ChOracle: A Unified Statistical Framework for Churn Prediction

no code implementations15 Sep 2019 Ali Khodadadi, Seyed Abbas Hosseini, Ehsan Pajouheshgar, Farnam Mansouri, Hamid R. Rabiee

In this approach which is more realistic in real world online services, at each time-step the model predicts the user return time instead of predicting a churn label.

Binary Classification Point Processes

Parallel Integer Polynomial Multiplication

no code implementations17 Dec 2016 Changbo Chen, Svyatoslav Covanov, Farnam Mansouri, Marc Moreno Maza, Ning Xie, Yuzhen Xie

We propose a new algorithm for multiplying dense polynomials with integer coefficients in a parallel fashion, targeting multi-core processor architectures.

Symbolic Computation Mathematical Software

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