Valentina Zantedeschi
17 papers · 2016–2026 · 8 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
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🗺️ Taxonomy Completionist (42) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
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Grand Slam
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Keyword Champion
(3)
📈
Trend Setter
🌈
Renaissance Researcher
(5)
💎
Century Club · Bronze
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Unstoppable · Bronze
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Keyword Collector
(99)
Top co-authors
Research topics
Machine Learning
(16)
Optimization & Theory · Machine Learning
(10)
Deep Learning
(7)
Artificial Intelligence
(6)
Core Methods
(5)
Learning Types · Machine Learning
(5)
Core AI
(4)
Application Areas
(3)
Architectures
(3)
Learning Types · Deep Learning
(2)
Optimization & Theory · Deep Learning
(2)
Computer Vision
(1)
Data Science & Analytics
(1)
Interdisciplinary
(1)
Natural Language Processing
(1)
Keywords
generalization bound
(4)
pac-bayes theory
(3)
large language model
(2)
transformer architecture
(2)
sample compression
(2)
probabilistic forecasting
(2)
ensemble learning
(1)
similarity learning
(1)
semi-supervised learning
(1)
causal discovery
(1)
multi-instance learning
(1)
weakly supervised learning
(1)
question answering
(1)
language modeling
(1)
metric learning
(1)
deep learning
(1)
language model evaluation
(1)
decision making
(1)
continuous optimization
(1)
document understanding
(1)
Papers
Bound to Disagree: Generalization Bounds via Certifiable Surrogates
UAI 2026
Context is Key: A Benchmark for Forecasting with Essential Textual Information
ICML 2025
InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation
ICLR 2025
Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses
AISTATS 2025
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures
AISTATS 2024
RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content
NeurIPS 2024
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series
ICLR 2024
XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference
EMNLP 2024
DAG Learning on the Permutahedron
ICLR 2023
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts
ICML 2023
On Margins and Generalisation for Voting Classifiers
NeurIPS 2022
Learning Binary Decision Trees by Argmin Differentiation
ICML 2021
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound
NeurIPS 2021
RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery
AAAI 2021
Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs
AISTATS 2020
beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data
NeurIPS 2016
Metric Learning as Convex Combinations of Local Models With Generalization Guarantees
CVPR 2016