Mario Marchand
20 papers · 2002–2024 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+10 more ↓ Show less ↑
🗺️ Taxonomy Completionist (41) 🏃 Academic Marathon · Ultra 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
🌟
Keyword Trendsetter Combo
(7)
🤝
Dynamic Duo
(10)
🔬
Deep Specialist
(10)
🏆
Keyword Champion
🧭
Keyword Pioneer
🚀
Conference Pioneer
🗃️
Keyword Collector
(102)
🔥
Unstoppable · Bronze
💎
Century Club · Bronze
📈
Trend Setter
Top co-authors
Research topics
Machine Learning
(19)
Optimization & Theory
(18)
Core Methods
(10)
Learning Types · Machine Learning
(7)
Artificial Intelligence
(6)
Deep Learning
(3)
Bayesian & Probabilistic · Machine Learning
(3)
Learning Types · Deep Learning
(3)
Mathematics & Optimization
(2)
Application Areas
(2)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Core AI
(2)
Learning Paradigms · Artificial Intelligence
(2)
Learning Paradigms · Machine Learning
(1)
Mathematics
(1)
Keywords
pac-bayes bound
(4)
ensemble learning
(4)
risk bound
(4)
model selection
(3)
generalization error
(3)
set covering machine
(2)
classifier ensemble
(2)
sample compression
(2)
learning theory
(2)
support vector machine
(2)
feature attribution
(2)
decision tree
(2)
generalization bound
(2)
bayesian inference
(2)
local explanation
(2)
gibbs classifier
(2)
structured output prediction
(2)
convex optimization
(1)
catastrophic forgetting
(1)
classification
(1)
Papers
Tackling the XAI Disagreement Problem with Regional Explanations
AISTATS 2024
Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain Adaptation
AISTATS 2023
Fooling SHAP with Stealthily Biased Sampling
ICLR 2023
On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm
NeurIPS 2023
Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon Set
JMLR 2023
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis
NeurIPS 2021
Decision trees as partitioning machines to characterize their generalization properties
NeurIPS 2020
A Column Generation Bound Minimization Approach with PAC-Bayesian Generalization Guarantees
AISTATS 2016
Algorithms for the Hard Pre-Image Problem of String Kernels and the General Problem of String Prediction
ICML 2015
Agnostic Bayesian Learning of Ensembles
ICML 2014
Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks
NeurIPS 2014
Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction
ICML 2013
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets
AISTATS 2012
From PAC-Bayes Bounds to KL Regularization
NeurIPS 2009
PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers
JMLR 2007
Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data
JMLR 2007
A PAC-Bayes Risk Bound for General Loss Functions
NeurIPS 2006
PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier
NeurIPS 2006
Learning with Decision Lists of Data-Dependent Features
JMLR 2005
The Set Covering Machine
JMLR 2002