Chris J. Maddison
14 papers · 2019–2025 · 4 venues · across top CS/AI venues
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Achievements
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🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (36) 🌍 Conference Polyglot · Bronze 🐣 Hot Topic Early Bird 🏃 Academic Marathon · Sprint
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Triple Crown
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Prolific Year · Productive
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Unstoppable · Bronze
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Century Club · Bronze
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Keyword Collector
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Research topics
Machine Learning
(13)
Optimization & Theory
(9)
Artificial Intelligence
(7)
Core AI
(6)
Deep Learning
(5)
Models
(4)
Natural Language Processing
(3)
Learning Types
(3)
Application Areas
(2)
Architectures
(2)
Core Methods
(2)
Learning Paradigms
(2)
Resources & Methods
(2)
Mathematics & Optimization
(1)
Applications
(1)
Keywords
large language model
(3)
convex optimization
(2)
variational inference
(2)
learning theory
(1)
epistemic uncertainty
(1)
domain adaptation
(1)
feature learning
(1)
variational inequality
(1)
calibration
(1)
natural language processing
(1)
ai safety
(1)
text mining
(1)
self-supervised learning
(1)
prompt engineering
(1)
causal effect estimation
(1)
contrastive learning
(1)
continuous optimization
(1)
gradient estimation
(1)
function space
(1)
representation learning
(1)
Papers
APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts
ACL 2025
MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures
ICLR 2025
MixMin: Finding Data Mixtures via Convex Minimization
ICML 2025
End-To-End Causal Effect Estimation from Unstructured Natural Language Data
NeurIPS 2024
Experts Don’t Cheat: Learning What You Don’t Know By Predicting Pairs
ICML 2024
Identifying the Risks of LM Agents with an LM-Emulated Sandbox
ICLR 2024
Observational Scaling Laws and the Predictability of Langauge Model Performance
NeurIPS 2024
On the Efficiency of ERM in Feature Learning
NeurIPS 2024
Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions
ICLR 2023
Optimal Representations for Covariate Shift
ICLR 2022
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator
ICLR 2021
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders
NeurIPS 2019
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
ICLR 2019
Hamiltonian descent for composite objectives
NeurIPS 2019