Valentina Zantedeschi
16 papers · 2016–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (9) π§ Keyword Pioneer π Interdisciplinary Bridge π Conference Polyglot (7) π Cross-Pollinator (11)
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Interdisciplinary Bridge
π§
Keyword Pioneer
π
Conference Polyglot
(7)
π
Grand Slam
π
Trend Setter
ποΈ
Keyword Collector
(71)
π
Century Club
(16)
π₯
Unstoppable
(6)
Conferences
NIPS (4)
AISTATS (3)
ICLR (3)
ICML (3)
AAAI (1)
CVPR (1)
EMNLP (1)
Top co-authors
Keywords
large language model
(2)
pac-bayes theory
(2)
generalization bound
(2)
benchmark evaluation
(1)
ensemble learning
(1)
statistical learning theory
(1)
semi-supervised learning
(1)
similarity learning
(1)
weakly supervised learning
(1)
question answering
(1)
language modeling
(1)
document understanding
(1)
language model evaluation
(1)
multi-modal learning
(1)
deep learning
(1)
multi-instance learning
(1)
majority vote
(1)
differentiable programming
(1)
communication efficiency
(1)
metric learning
(1)
Papers
Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses
AISTATS 2025
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
RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content
NIPS 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
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures
AISTATS 2024
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts
ICML 2023
DAG Learning on the Permutahedron
ICLR 2023
On Margins and Generalisation for Voting Classifiers
NIPS 2022
Learning Binary Decision Trees by Argmin Differentiation
ICML 2021
RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery
AAAI 2021
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound
NIPS 2021
Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs
AISTATS 2020
Metric Learning as Convex Combinations of Local Models With Generalization Guarantees
CVPR 2016
beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data
NIPS 2016