Search Results for author: Giovanni Paolini

Found 13 papers, 4 papers with code

Taxonomy Expansion for Named Entity Recognition

no code implementations22 May 2023 Karthikeyan K, Yogarshi Vyas, Jie Ma, Giovanni Paolini, Neha Anna John, Shuai Wang, Yassine Benajiba, Vittorio Castelli, Dan Roth, Miguel Ballesteros

We experiment with 6 diverse datasets and show that PLM consistently performs better than most other approaches (0. 5 - 2. 5 F1), including in novel settings for taxonomy expansion not considered in prior work.

named-entity-recognition Named Entity Recognition +2

A Weak Supervision Approach for Few-Shot Aspect Based Sentiment

no code implementations19 May 2023 Robert Vacareanu, Siddharth Varia, Kishaloy Halder, Shuai Wang, Giovanni Paolini, Neha Anna John, Miguel Ballesteros, Smaranda Muresan

We explore how weak supervision on abundant unlabeled data can be leveraged to improve few-shot performance in aspect-based sentiment analysis (ABSA) tasks.

Aspect-Based Sentiment Analysis Aspect Extraction +3

DIVA: Dataset Derivative of a Learning Task

no code implementations ICLR 2022 Yonatan Dukler, Alessandro Achille, Giovanni Paolini, Avinash Ravichandran, Marzia Polito, Stefano Soatto

A learning task is a function from a training set to the validation error, which can be represented by a trained deep neural network (DNN).


STRIC: Stacked Residuals of Interpretable Components for Time Series Anomaly Detection

no code implementations29 Sep 2021 Luca Zancato, Alessandro Achille, Giovanni Paolini, Alessandro Chiuso, Stefano Soatto

After modeling the signals, we use an anomaly detection system based on the classic CUMSUM algorithm and a variational approximation of the $f$-divergence to detect both isolated point anomalies and change-points in statistics of the signals.

Anomaly Detection Time Series +1

Factoring isometries of quadratic spaces into reflections

no code implementations3 Mar 2021 Jon McCammond, Giovanni Paolini

In particular, we show that an isometry is a product of positive reflections if and only if its spinor norm is positive.

Group Theory

Estimating informativeness of samples with Smooth Unique Information

1 code implementation ICLR 2021 Hrayr Harutyunyan, Alessandro Achille, Giovanni Paolini, Orchid Majumder, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto

We define a notion of information that an individual sample provides to the training of a neural network, and we specialize it to measure both how much a sample informs the final weights and how much it informs the function computed by the weights.


Structured Prediction as Translation between Augmented Natural Languages

1 code implementation ICLR 2021 Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, Rishita Anubhai, Cicero Nogueira dos santos, Bing Xiang, Stefano Soatto

We propose a new framework, Translation between Augmented Natural Languages (TANL), to solve many structured prediction language tasks including joint entity and relation extraction, nested named entity recognition, relation classification, semantic role labeling, event extraction, coreference resolution, and dialogue state tracking.

coreference-resolution Dialogue State Tracking +11

Where is the Information in a Deep Neural Network?

no code implementations29 May 2019 Alessandro Achille, Giovanni Paolini, Stefano Soatto

We establish a novel relation between the information in the weights and the effective information in the activations, and use this result to show that models with low (information) complexity not only generalize better, but are bound to learn invariant representations of future inputs.

Inductive Bias Open-Ended Question Answering

The Information Complexity of Learning Tasks, their Structure and their Distance

no code implementations5 Apr 2019 Alessandro Achille, Giovanni Paolini, Glen Mbeng, Stefano Soatto

Our framework is the first to measure complexity in a way that accounts for the effect of the optimization scheme, which is critical in Deep Learning.

Memorization Transfer Learning

Impossibility results on stability of phylogenetic consensus methods

1 code implementation8 Oct 2018 Emanuele Delucchi, Linard Hoessly, Giovanni Paolini

We answer two questions raised by Bryant, Francis and Steel in their work on consensus methods in phylogenetics.

On the local homology of Artin groups of finite and affine type

1 code implementation5 Sep 2017 Giovanni Paolini

In all finite and affine cases, we are able to construct Morse matchings of a special type (we call them "precise matchings").

Algebraic Topology Combinatorics Group Theory

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