Poorya Mianjy
13 papers · 2016–2023 · 3 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (21) π Academic Marathon Β· Sprint π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π€
Dynamic Duo
(13)
π
Triple Crown
β‘
Prolific Year Β· Productive
π₯
Unstoppable Β· Bronze
π
Century Club Β· Bronze
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Conference Pioneer
ποΈ
Keyword Collector
(55)
Venues
Top co-authors
Research topics
Machine Learning
(13)
Optimization & Theory Β· Machine Learning
(13)
Deep Learning
(7)
Core Methods
(6)
Learning Types Β· Machine Learning
(5)
Architectures
(3)
Learning Types Β· Deep Learning
(3)
Techniques
(3)
Mathematics & Optimization
(2)
Optimization
(2)
Optimization & Theory Β· Deep Learning
(2)
Keywords
neural network
(6)
principal component analysis
(3)
stochastic gradient descent
(3)
learning theory
(2)
adversarial attack
(2)
generalization bound
(2)
robust optimization
(2)
streaming algorithm
(2)
data poisoning
(1)
outlier detection
(1)
adversarial robustness
(1)
kernel pca
(1)
convex relaxation
(1)
canonical correlation analysis
(1)
adversarial training
(1)
optimization landscape
(1)
convergence analysis
(1)
matrix completion
(1)
stochastic approximation
(1)
rademacher complexity
(1)
Papers
Robustness Guarantees for Adversarially Trained Neural Networks
NeurIPS 2023
Adversarial Robustness is at Odds with Lazy Training
NeurIPS 2022
Dropout: Explicit Forms and Capacity Control
ICML 2021
Robust Learning for Data Poisoning Attacks
ICML 2021
On Convergence and Generalization of Dropout Training
NeurIPS 2020
On Dropout and Nuclear Norm Regularization
ICML 2019
On the Implicit Bias of Dropout
ICML 2018
Stochastic PCA with β_2 and β_1 Regularization
ICML 2018
Streaming Kernel PCA with OΜ(βn) Random Features
NeurIPS 2018
Streaming Principal Component Analysis in Noisy Setting
ICML 2018
Understanding Deep Neural Networks with Rectified Linear Units
ICLR 2018
Stochastic Approximation for Canonical Correlation Analysis
NeurIPS 2017
Stochastic Optimization for Multiview Representation Learning using Partial Least Squares
ICML 2016