activity
20122020
most citedMachine Learning at Microsoft with ML .NET

53 citations · 87 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG202025 cited

Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning"

Saeed Amizadeh, Hamid Palangi, Oleksandr Polozov +2

Visual reasoning tasks such as visual question answering (VQA) require an interplay of visual perception with reasoning about the question semantics grounded in perception. However…

cs.LG2019

Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach

Gyeong-In Yu, Saeed Amizadeh, Sehoon Kim +4

Classical Machine Learning (ML) pipelines often comprise of multiple ML models where models, within a pipeline, are trained in isolation. Conversely, when training neural network m…

cs.LG201953 cited

Machine Learning at Microsoft with ML .NET

Zeeshan Ahmed, Saeed Amizadeh, Mikhail Bilenko +31

Machine Learning is transitioning from an art and science into a technology available to every developer. In the near future, every application on every platform will incorporate t…

cs.LG20197 cited

PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers

Saeed Amizadeh, Sergiy Matusevych, Markus Weimer

There have been recent efforts for incorporating Graph Neural Network models for learning full-stack solvers for constraint satisfaction problems (CSP) and particularly Boolean sat…

cs.IT2018

Coded Elastic Computing

Yaoqing Yang, Matteo Interlandi, Pulkit Grover +3

Cloud providers have recently introduced new offerings whereby spare computing resources are accessible at discounts compared to on-demand computing. Exploiting such opportunity is…

cs.LG20122 cited

Variational Dual-Tree Framework for Large-Scale Transition Matrix Approximation

Saeed Amizadeh, Bo Thiesson, Milos Hauskrecht

In recent years, non-parametric methods utilizing random walks on graphs have been used to solve a wide range of machine learning problems, but in their simplest form they do not s…