Saeed Amizadeh

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 13

Top Topics

Machine Learning

Top Venues

Proc. VLDB Endow.

Publications

Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida, Diana Marculescu
Weakly-supervised Audio Separation via Bi-modal Semantic Similarity. ICLR (2024)
Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida, Diana Marculescu
Weakly-supervised Audio Separation via Bi-modal Semantic Similarity. CoRR (2024)
Gyeong-In Yu, Saeed Amizadeh, Sehoon Kim, Artidoro Pagnoni, Ce Zhang, Byung-Gon Chun, Markus Weimer, Matteo Interlandi
WindTunnel: Towards Differentiable ML Pipelines Beyond a Single Modele. Proc. VLDB Endow. 15 (1) (2021)
Saeed Amizadeh, Hamid Palangi, Alex Polozov, Yichen Huang, Kazuhito Koishida
Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning". ICML (2020)
Saeed Amizadeh, Hamid Palangi, Oleksandr Polozov, Yichen Huang, Kazuhito Koishida
Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning". CoRR (2020)
Yaoqing Yang, Matteo Interlandi, Pulkit Grover, Soummya Kar, Saeed Amizadeh, Markus Weimer
Coded Elastic Computing. ISIT (2019)
Zeeshan Ahmed, Saeed Amizadeh, Mikhail Bilenko, Rogan Carr, Wei-Sheng Chin, Yael Dekel, Xavier Dupré, Vadim Eksarevskiy, Senja Filipi, Tom Finley, Abhishek Goswami, Monte Hoover, Scott Inglis, Matteo Interlandi, Najeeb Kazmi, Gleb Krivosheev, Pete Luferenko, Ivan Matantsev, Sergiy Matusevych, Shahab Moradi, Gani Nazirov, Justin Ormont, Gal Oshri, Artidoro Pagnoni, Jignesh Parmar, Prabhat Roy, Mohammad Zeeshan Siddiqui, Markus Weimer, Shauheen Zahirazami, Yiwen Zhu
Machine Learning at Microsoft with ML.NET. KDD (2019)
Zeeshan Ahmed, Saeed Amizadeh, Mikhail Bilenko, Rogan Carr, Wei-Sheng Chin, Yael Dekel, Xavier Dupré, Vadim Eksarevskiy, Eric Erhardt, Costin Eseanu, Senja Filipi, Tom Finley, Abhishek Goswami, Monte Hoover, Scott Inglis, Matteo Interlandi, Shon Katzenberger, Najeeb Kazmi, Gleb Krivosheev, Pete Luferenko, Ivan Matantsev, Sergiy Matusevych, Shahab Moradi, Gani Nazirov, Justin Ormont, Gal Oshri, Artidoro Pagnoni, Jignesh Parmar, Prabhat Roy, Sarthak Shah, Mohammad Zeeshan Siddiqui, Markus Weimer, Shauheen Zahirazami, Yiwen Zhu
Machine Learning at Microsoft with ML .NET. CoRR (2019)
Saeed Amizadeh, Sergiy Matusevych, Markus Weimer
Learning To Solve Circuit-SAT: An Unsupervised Differentiable Approach. ICLR (Poster) (2019)
Saeed Amizadeh, Sergiy Matusevych, Markus Weimer
PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers. CoRR (2019)
Gyeong-In Yu, Saeed Amizadeh, Artidoro Pagnoni, Byung-Gon Chun, Markus Weimer, Matteo Interlandi
Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach. CoRR (2019)
Chenggang Wu, Alekh Jindal, Saeed Amizadeh, Hiren Patel, Wangchao Le, Shi Qiao, Sriram Rao
Towards a Learning Optimizer for Shared Clouds. Proc. VLDB Endow. 12 (3) (2018)
Yaoqing Yang, Matteo Interlandi, Pulkit Grover, Soummya Kar, Saeed Amizadeh, Markus Weimer
Coded Elastic Computing. CoRR (2018)
George D. Montañez, Saeed Amizadeh, Nikolay Laptev
Inertial Hidden Markov Models: Modeling Change in Multivariate Time Series. AAAI (2015)
Nikolay Laptev, Saeed Amizadeh, Ian Flint
Generic and Scalable Framework for Automated Time-series Anomaly Detection. KDD (2015)
Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht
The Bregman Variational Dual-Tree Framework. UAI (2013)
Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht
The Bregman Variational Dual-Tree Framework. CoRR (2013)
Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht
Variational Dual-Tree Framework for Large-Scale Transition Matrix Approximation. UAI (2012)
Hadi Firouzi, Majid Nili Ahmadabadi, Babak Nadjar Araabi, Saeed Amizadeh, Maryam S. Mirian, Roland Siegwart
Interactive Learning in Continuous Multimodal Space: A Bayesian Approach to Action-Based Soft Partitioning and Learning. IEEE Trans. Auton. Ment. Dev. 4 (2) (2012)
Hamed Valizadegan, Saeed Amizadeh, Milos Hauskrecht
Sampling Strategies to Evaluate the Performance of Unknown Predictors. SDM (2012)
Saeed Amizadeh, Hamed Valizadegan, Milos Hauskrecht
Factorized Diffusion Map Approximation. AISTATS (2012)
Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht
Variational Dual-Tree Framework for Large-Scale Transition Matrix Approximation CoRR (2012)
Saeed Amizadeh, Shuguang Wang, Milos Hauskrecht
An Efficient Framework for Constructing Generalized Locally-Induced Text Metrics. IJCAI (2011)
Saeed Amizadeh, Milos Hauskrecht
Latent Variable Model for Learning in Pairwise Markov Networks. AAAI (2010)