no code implementations • 21 Aug 2023 • Saeed Masoudian, Julian Zimmert, Yevgeny Seldin
Another major contribution is demonstrating that the complexity of best-of-both-worlds bandits with delayed feedback is characterized by the cumulative count of outstanding observations after skipping of observations with excessively large delays, rather than the delays or the maximal delay.
no code implementations • 30 May 2023 • Emmanuel Esposito, Saeed Masoudian, Hao Qiu, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin
However, if the mapping of states to losses is stochastic, we show that the regret grows at a rate of $\sqrt{\big(K+\min\{|\mathcal{S}|, d\}\big)T}$ (within log factors), implying that if the number $|\mathcal{S}|$ of states is smaller than the delay, then intermediate observations help.
no code implementations • 29 Jun 2022 • Saeed Masoudian, Julian Zimmert, Yevgeny Seldin
We present a modified tuning of the algorithm of Zimmert and Seldin [2020] for adversarial multiarmed bandits with delayed feedback, which in addition to the minimax optimal adversarial regret guarantee shown by Zimmert and Seldin simultaneously achieves a near-optimal regret guarantee in the stochastic setting with fixed delays.
no code implementations • 23 Mar 2021 • Saeed Masoudian, Yevgeny Seldin
We derive improved regret bounds for the Tsallis-INF algorithm of Zimmert and Seldin (2021).
no code implementations • 23 Nov 2020 • Rassa Ghavami Modegh, Mehrab Hamidi, Saeed Masoudian, Amir Mohseni, Hamzeh Lotfalinezhad, Mohammad Ali Kazemi, Behnaz Moradi, Mahyar Ghafoori, Omid Motamedi, Omid Pournik, Kiara Rezaei-Kalantari, Amirreza Manteghinezhad, Shaghayegh Haghjooy Javanmard, Fateme Abdoli Nezhad, Ahmad Enhesari, Mohammad Saeed Kheyrkhah, Razieh Eghtesadi, Javid Azadbakht, Akbar Aliasgharzadeh, Mohammad Reza Sharif, Ali Khaleghi, Abbas Foroutan, Hossein Ghanaati, Hamed Dashti, Hamid R. Rabiee
We designed a new interpretable deep neural network to distinguish healthy people, patients with COVID-19, and patients with other pneumonia diseases from axial lung CT-scan images.
no code implementations • 1 Jun 2019 • Saeed Masoudian, Ali Arabzadeh, Mahdi Jafari Siavoshani, Milad Jalal, Alireza Amouzad
Finally, as a representative application of our proposed algorithm, we study the problem of learning the best regularizer from a family of regularizers for Online Mirror Descent.
