Search Results for author: Alona Fyshe

Found 29 papers, 4 papers with code

Language and Mental Health: Measures of Emotion Dynamics from Text as Linguistic Biosocial Markers

no code implementations26 Oct 2023 Daniela Teodorescu, Tiffany Cheng, Alona Fyshe, Saif M. Mohammad

Research in psychopathology has shown that, at an aggregate level, the patterns of emotional change over time -- emotion dynamics -- are indicators of one's mental health.

Utterance Emotion Dynamics in Children's Poems: Emotional Changes Across Age

no code implementations8 Jun 2023 Daniela Teodorescu, Alona Fyshe, Saif M. Mohammad

These results act as a useful baselines for further research in how patterns of emotions expressed by children change with age, and their association with mental health.

Identifying Shared Decodable Concepts in the Human Brain Using Image-Language Foundation Models

no code implementations6 Jun 2023 Cory Efird, Alex Murphy, Joel Zylberberg, Alona Fyshe

In the final section of our analysis, we localize shared decodable concepts in the brain using a voxel-masking optimization method to produce a shared decodable concept (SDC) space.

Contrastive Learning Dimensionality Reduction

DISTO: Evaluating Textual Distractors for Multi-Choice Questions using Negative Sampling based Approach

no code implementations10 Apr 2023 Bilal Ghanem, Alona Fyshe

At the same time, DISTO ranks the performance of state-of-the-art DG models very differently from MT-based metrics, showing that MT metrics should not be used for distractor evaluation.

Distractor Generation Machine Translation +3

Weakly-Supervised Questions for Zero-Shot Relation Extraction

1 code implementation21 Jan 2023 Saeed Najafi, Alona Fyshe

Zero-Shot Relation Extraction (ZRE) is the task of Relation Extraction where the training and test sets have no shared relation types.

Question Answering Relation +1

Improving the Accuracy and Robustness of CNNs Using a Deep CCA Neural Data Regularizer

no code implementations6 Sep 2022 Cassidy Pirlot, Richard C. Gerum, Cory Efird, Joel Zylberberg, Alona Fyshe

As convolutional neural networks (CNNs) become more accurate at object recognition, their representations become more similar to the primate visual system.

Object Recognition

Different Spectral Representations in Optimized Artificial Neural Networks and Brains

1 code implementation22 Aug 2022 Richard C. Gerum, Cassidy Pirlot, Alona Fyshe, Joel Zylberberg

For convolutional networks, the best $\alpha$ values depend on the task complexity and evaluation metric: lower $\alpha$ values optimized validation accuracy and robustness to adversarial attack for networks performing a simple object recognition task (categorizing MNIST images of handwritten digits); for a more complex task (categorizing CIFAR-10 natural images), we found that lower $\alpha$ values optimized validation accuracy whereas higher $\alpha$ values optimized adversarial robustness.

Adversarial Attack Adversarial Robustness +1

Long Term Fairness for Minority Groups via Performative Distributionally Robust Optimization

no code implementations12 Jul 2022 Liam Peet-Pare, Nidhi Hegde, Alona Fyshe

Fairness researchers in machine learning (ML) have coalesced around several fairness criteria which provide formal definitions of what it means for an ML model to be fair.

BIG-bench Machine Learning Fairness

Predictive Representation Learning for Language Modeling

no code implementations29 May 2021 Qingfeng Lan, Luke Kumar, Martha White, Alona Fyshe

Correlates of secondary information appear in LSTM representations even though they are not part of an \emph{explicitly} supervised prediction task.

Language Modelling Reinforcement Learning (RL) +1

Maxmin Q-learning: Controlling the Estimation Bias of Q-learning

1 code implementation ICLR 2020 Qingfeng Lan, Yangchen Pan, Alona Fyshe, Martha White

Q-learning suffers from overestimation bias, because it approximates the maximum action value using the maximum estimated action value.

Q-Learning

Improved object recognition using neural networks trained to mimic the brain's statistical properties

1 code implementation25 May 2019 Callie Federer, Haoyan Xu, Alona Fyshe, Joel Zylberberg

To test this, we trained DCNNs on a composite task, wherein networks were trained to: a) classify images of objects; while b) having intermediate representations that resemble those observed in neural recordings from monkey visual cortex.

Object Object Categorization +2

Interpreting Word-Level Hidden State Behaviour of Character-Level LSTM Language Models

no code implementations WS 2018 Avery Hiebert, Cole Peterson, Alona Fyshe, Nishant Mehta

While Long Short-Term Memory networks (LSTMs) and other forms of recurrent neural network have been successfully applied to language modeling on a character level, the hidden state dynamics of these models can be difficult to interpret.

Clustering Language Modelling +1

Using Word Embeddings to Explore the Learned Representations of Convolutional Neural Networks

no code implementations27 Sep 2018 Dhanush Dharmaretnam, Chris Foster, Alona Fyshe

Here we build on previous work that indicated that two very different model classes trained on two very different tasks actually build knowledge representations that have similar underlying representations.

Adversarial Attack Image Classification +1

Ensemble Methods for Native Language Identification

no code implementations WS 2017 Sophia Chan, Maryam Honari Jahromi, Benjamin Benetti, Aazim Lakhani, Alona Fyshe

Our team{---}Uvic-NLP{---}explored and evaluated a variety of lexical features for Native Language Identification (NLI) within the framework of ensemble methods.

Language Acquisition Native Language Identification

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