Christoph Lampert
12 papers · 2013–2024 · 4 venues · across top CS/AI venues
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Achievements
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🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (29) 🌍 Conference Polyglot · Bronze 🐣 Hot Topic Early Bird 🏃 Academic Marathon · Half
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Conference Pioneer
❓
The Questioner
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Century Club · Bronze
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Machine Learning
(12)
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(9)
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(5)
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(3)
Core Methods
(3)
Deep Learning
(2)
Learning Paradigms
(2)
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(2)
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(1)
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(1)
Security & Privacy
(1)
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(1)
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(1)
Bayesian & Probabilistic
(1)
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(1)
Keywords
generalization bound
(4)
neural network
(2)
transfer learning
(2)
stochastic gradient descent
(2)
convex optimization
(1)
probabilistic modeling
(1)
non-convex optimization
(1)
pac learning
(1)
online learning
(1)
domain adaptation
(1)
multi-source learning
(1)
structured prediction
(1)
matrix factorization
(1)
statistical learning theory
(1)
object detection
(1)
probabilistic inference
(1)
knowledge distillation
(1)
sample complexity
(1)
domain generalization
(1)
adversarial learning
(1)
Papers
Banded Square Root Matrix Factorization for Differentially Private Model Training
NeurIPS 2024
Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?
NeurIPS 2024
A Flexible Selection Scheme for Minimum-Effort Transfer Learning
WACV 2020
Localizing Grouped Instances for Efficient Detection in Low-Resource Scenarios
WACV 2020
On the Sample Complexity of Adversarial Multi-Source PAC Learning
ICML 2020
Robust Learning from Untrusted Sources
ICML 2019
Towards Understanding Knowledge Distillation
ICML 2019
Data-Dependent Stability of Stochastic Gradient Descent
ICML 2018
Learning Equations for Extrapolation and Control
ICML 2018
Learning Theory for Conditional Risk Minimization
AISTATS 2017
A PAC-Bayesian bound for Lifelong Learning
ICML 2014
Computing the M Most Probable Modes of a Graphical Model
AISTATS 2013