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Saeed Amizadeh
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2020 – today
- 2024
- [c13]Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida, Diana Marculescu:
Weakly-supervised Audio Separation via Bi-modal Semantic Similarity. ICLR 2024 - [i8]Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida, Diana Marculescu:
Weakly-supervised Audio Separation via Bi-modal Semantic Similarity. CoRR abs/2404.01740 (2024) - 2021
- [j3]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): 11-20 (2021) - 2020
- [c12]Saeed Amizadeh, Hamid Palangi, Alex Polozov, Yichen Huang
, Kazuhito Koishida:
Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning". ICML 2020: 279-290 - [i7]Saeed Amizadeh, Hamid Palangi, Oleksandr Polozov, Yichen Huang, Kazuhito Koishida:
Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning". CoRR abs/2006.11524 (2020)
2010 – 2019
- 2019
- [c11]Saeed Amizadeh, Sergiy Matusevych, Markus Weimer:
Learning To Solve Circuit-SAT: An Unsupervised Differentiable Approach. ICLR (Poster) 2019 - [c10]Yaoqing Yang, Matteo Interlandi, Pulkit Grover
Coded Elastic Computing. ISIT 2019: 2654-2658 - [c9]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
Machine Learning at Microsoft with ML.NET. KDD 2019: 2448-2458 - [i6]Saeed Amizadeh, Sergiy Matusevych, Markus Weimer:
PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers. CoRR abs/1903.01969 (2019) - [i5]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 abs/1905.05715 (2019) - [i4]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 abs/1906.03822 (2019) - 2018
- [j2]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): 210-222 (2018) - [i3]Yaoqing Yang, Matteo Interlandi, Pulkit Grover
Coded Elastic Computing. CoRR abs/1812.06411 (2018) - 2015
- [c8]George D. Montañez, Saeed Amizadeh, Nikolay Laptev:
Inertial Hidden Markov Models: Modeling Change in Multivariate Time Series. AAAI 2015: 1819-1825 - [c7]Nikolay Laptev, Saeed Amizadeh, Ian Flint:
Generic and Scalable Framework for Automated Time-series Anomaly Detection. KDD 2015: 1939-1947 - 2013
- [c6]Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht:
The Bregman Variational Dual-Tree Framework. UAI 2013 - [i2]Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht:
The Bregman Variational Dual-Tree Framework. CoRR abs/1309.6812 (2013) - 2012
- [j1]Hadi Firouzi, Majid Nili Ahmadabadi, Babak Nadjar Araabi
Interactive Learning in Continuous Multimodal Space: A Bayesian Approach to Action-Based Soft Partitioning and Learning. IEEE Trans. Auton. Ment. Dev. 4(2): 124-138 (2012) - [c5]Hamed Valizadegan, Saeed Amizadeh, Milos Hauskrecht:
Sampling Strategies to Evaluate the Performance of Unknown Predictors. SDM 2012: 494-505 - [c4]Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht:
Variational Dual-Tree Framework for Large-Scale Transition Matrix Approximation. UAI 2012: 64-73 - [c3]Saeed Amizadeh, Hamed Valizadegan, Milos Hauskrecht:
Factorized Diffusion Map Approximation. AISTATS 2012: 37-46 - [i1]Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht:
Variational Dual-Tree Framework for Large-Scale Transition Matrix Approximation. CoRR abs/1210.4846 (2012) - 2011
- [c2]Saeed Amizadeh, Shuguang Wang, Milos Hauskrecht:
An Efficient Framework for Constructing Generalized Locally-Induced Text Metrics. IJCAI 2011: 1159-1164 - 2010
- [c1]Saeed Amizadeh, Milos Hauskrecht:
Latent Variable Model for Learning in Pairwise Markov Networks. AAAI 2010: 382-387
Coauthor Index
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last updated on 2024-10-07 22:20 CEST by the dblp team
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