Alexander Ororbia

According to our database1, Alexander Ororbia authored at least 88 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
A neural active inference model of perceptual-motor learning.
Frontiers Comput. Neurosci., February, 2023

Backpropagation-Free 4D Continuous Ant-Based Neural Topology Search.
CoRR, 2023

Learning Spiking Neural Systems with the Event-Driven Forward-Forward Process.
CoRR, 2023

Predicted Embedding Power Regression for Large-Scale Out-of-Distribution Detection.
CoRR, 2023

Online Evolutionary Neural Architecture Search for Multivariate Non-Stationary Time Series Forecasting.
CoRR, 2023

The Predictive Forward-Forward Algorithm.
CoRR, 2023

2022
Convolutional Neural Generative Coding: Scaling Predictive Coding to Natural Images.
CoRR, 2022

Active Predicting Coding: Brain-Inspired Reinforcement Learning for Sparse Reward Robotic Control Problems.
CoRR, 2022

A Robust Backpropagation-Free Framework for Images.
CoRR, 2022

CogNGen: Constructing the Kernel of a Hyperdimensional Predictive Processing Cognitive Architecture.
CoRR, 2022

Lifelong Neural Predictive Coding: Learning Cumulatively Online without Forgetting.
NeurIPS, 2022

Multimodal Modeling of Task-Mediated Confusion.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop, 2022

Improving Label Quality by Jointly Modeling Items and Annotators.
Proceedings of the 1st Workshop on Perspectivist Approaches to NLPerspectives@LREC 2022, 2022

Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder.
Proceedings of the Data Compression Conference, 2022

Maze Learning Using a Hyperdimensional Predictive Processing Cognitive Architecture.
Proceedings of the Artificial General Intelligence - 15th International Conference, 2022

Reducing Catastrophic Forgetting in Self Organizing Maps with Internally-Induced Generative Replay (Student Abstract).
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Backprop-Free Reinforcement Learning with Active Neural Generative Coding.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Reducing Catastrophic Forgetting in Self Organizing Maps with Internally-Induced Generative Replay.
CoRR, 2021

Continual Competitive Memory: A Neural System for Online Task-Free Lifelong Learning.
CoRR, 2021

Towards a Predictive Processing Implementation of the Common Model of Cognition.
CoRR, 2021

WLV-RIT at SemEval-2021 Task 5: A Neural Transformer Framework for Detecting Toxic Spans.
Proceedings of the 15th International Workshop on Semantic Evaluation, 2021

Investigating Backpropagation Alternatives when Learning to Dynamically Count with Recurrent Neural Networks.
Proceedings of the 15th International Conference on Grammatical Inference, 2021

Recognizing Long Grammatical Sequences using Recurrent Networks Augmented with an External Differentiable Stack.
Proceedings of the 15th International Conference on Grammatical Inference, 2021

Continuous Ant-Based Neural Topology Search.
Proceedings of the Applications of Evolutionary Computation, 2021

fBERT: A Neural Transformer for Identifying Offensive Content.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

An Empirical Analysis of Recurrent Learning Algorithms in Neural Lossy Image Compression Systems.
Proceedings of the 31st Data Compression Conference, 2021

Eliciting Confusion in Online Conversational Tasks.
Proceedings of the 2021 9th International Conference on Affective Computing and Intelligent Interaction, 2021

Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Investigating Deep Recurrent Connections and Recurrent Memory Cells Using Neuro-Evolution.
Proceedings of the Deep Neural Evolution - Deep Learning with Evolutionary Computation, 2020

Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations.
IEEE Trans. Neural Networks Learn. Syst., 2020

A Neural State Pushdown Automata.
IEEE Trans. Artif. Intell., 2020

The Neural Coding Framework for Learning Generative Models.
CoRR, 2020

Neuroevolutionary Transfer Learning of Deep Recurrent Neural Networks through Network-Aware Adaptation.
CoRR, 2020

Reducing the Computational Burden of Deep Learning with Recursive Local Representation Alignment.
CoRR, 2020

Improving neuroevolutionary transfer learning of deep recurrent neural networks through network-aware adaptation.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Ant-based Neural Topology Search (ANTS) for Optimizing Recurrent Networks.
Proceedings of the Applications of Evolutionary Computation - 23rd European Conference, 2020

Neuro-Evolutionary Transfer Learning Through Structural Adaptation.
Proceedings of the Applications of Evolutionary Computation - 23rd European Conference, 2020

An Empirical Exploration of Deep Recurrent Connections Using Neuro-Evolution.
Proceedings of the Applications of Evolutionary Computation - 23rd European Conference, 2020

The Sibling Neural Estimator: Improving Iterative Image Decoding with Gradient Communication.
Proceedings of the Data Compression Conference, 2020

2019
Sibling Neural Estimators: Improving Iterative Image Decoding with Gradient Communication.
CoRR, 2019

The Ant Swarm Neuro-Evolution Procedure for Optimizing Recurrent Networks.
CoRR, 2019

An Empirical Exploration of Deep Recurrent Connections and Memory Cells Using Neuro-Evolution.
CoRR, 2019

Spiking Neural Predictive Coding for Continual Learning from Data Streams.
CoRR, 2019

A Hybrid Algorithm for Metaheuristic Optimization.
CoRR, 2019

Lifelong Neural Predictive Coding: Sparsity Yields Less Forgetting when Learning Cumulatively.
CoRR, 2019

Column2Vec: Structural Understanding via Distributed Representations of Database Schemas.
CoRR, 2019

Investigating Recurrent Neural Network Memory Structures using Neuro-Evolution.
CoRR, 2019

Investigating recurrent neural network memory structures using neuro-evolution.
Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Learned Neural Iterative Decoding for Lossy Image Compression Systems.
Proceedings of the Data Compression Conference, 2019

A Neural Temporal Model for Human Motion Prediction.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Like a Baby: Visually Situated Neural Language Acquisition.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Biologically Motivated Algorithms for Propagating Local Target Representations.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
An Empirical Evaluation of Rule Extraction from Recurrent Neural Networks.
Neural Comput., 2018

Online Learning of Recurrent Neural Architectures by Locally Aligning Distributed Representations.
CoRR, 2018

Visually Grounded, Situated Learning in Neural Models.
CoRR, 2018

Learned Iterative Decoding for Lossy Image Compression Systems.
CoRR, 2018

Conducting Credit Assignment by Aligning Local Representations.
CoRR, 2018

A Comparison of Rule Extraction for Different Recurrent Neural Network Models and Grammatical Complexity.
CoRR, 2018

Defending Against Adversarial Samples Without Security through Obscurity.
Proceedings of the IEEE International Conference on Data Mining, 2018

Learning a Hierarchical Latent-Variable Model of 3D Shapes.
Proceedings of the 2018 International Conference on 3D Vision, 2018

2017
Learning Simpler Language Models with the Differential State Framework.
Neural Comput., 2017

Unifying Adversarial Training Algorithms with Data Gradient Regularization.
Neural Comput., 2017

Learning to Adapt by Minimizing Discrepancy.
CoRR, 2017

An Empirical Evaluation of Recurrent Neural Network Rule Extraction.
CoRR, 2017

Learning Simpler Language Models with the Delta Recurrent Neural Network Framework.
CoRR, 2017

Learning a Hierarchical Latent-Variable Model of Voxelized 3D Shapes.
CoRR, 2017

Adversary Resistant Deep Neural Networks with an Application to Malware Detection.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Smart Library: Identifying Books on Library Shelves Using Supervised Deep Learning for Scene Text Reading.
Proceedings of the 2017 ACM/IEEE Joint Conference on Digital Libraries, 2017

Event Ordering with a Generalized Model for Sieve Prediction Ranking.
Proceedings of the Eighth International Joint Conference on Natural Language Processing, 2017

Piecewise Latent Variables for Neural Variational Text Processing.
Proceedings of the 2nd Workshop on Structured Prediction for Natural Language Processing, 2017

Multi-scale FCN with Cascaded Instance Aware Segmentation for Arbitrary Oriented Word Spotting in the Wild.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Smart Library: Identifying Books in a Library using Richly Supervised Deep Scene Text Reading.
CoRR, 2016

Learning Adversary-Resistant Deep Neural Networks.
CoRR, 2016

Using Non-invertible Data Transformations to Build Adversary-Resistant Deep Neural Networks.
CoRR, 2016

Multi-modal Variational Encoder-Decoders.
CoRR, 2016

Privacy Protection for Natural Language: Neural Generative Models for Synthetic Text Data.
CoRR, 2016

Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization.
CoRR, 2016

Using Prerequisites to Extract Concept Maps fromTextbooks.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015
Online Semi-Supervised Learning with Deep Hybrid Boltzmann Machines and Denoising Autoencoders.
CoRR, 2015

ExpertSeer: a Keyphrase Based Expert Recommender for Digital Libraries.
CoRR, 2015

CiteSeerX: AI in a Digital Library Search Engine.
AI Mag., 2015

Big Scholarly Data in CiteSeerX: Information Extraction from the Web.
Proceedings of the 24th International Conference on World Wide Web Companion, 2015

Error-Correction and Aggregation in Crowd-Sourcing of Geopolitical Incident Information.
Proceedings of the Social Computing, Behavioral-Cultural Modeling, and Prediction, 2015

Online Learning of Deep Hybrid Architectures for Semi-supervised Categorization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Learning a Deep Hybrid Model for Semi-Supervised Text Classification.
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015

2014
Towards building a scholarly big data platform: Challenges, lessons and opportunities.
Proceedings of the IEEE/ACM Joint Conference on Digital Libraries, 2014

Utility-Based Control Feedback in a Digital Library Search Engine: Cases in CiteSeerX.
Proceedings of the 9th International Workshop on Feedback Computing, 2014

CiteSeerX: AI in a Digital Library Search Engine.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014


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