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09/05/2023
Diffusion on the Probability Simplex
Diffusion models learn to reverse the progressive noising of a data dist...
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08/01/2023
Self-Supervised Contrastive BERT Fine-tuning for Fusion-based Reviewed-Item Retrieval
As natural language interfaces enable users to express increasingly comp...
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07/26/2023
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences
Traditional recommender systems leverage users' item preference history ...
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06/14/2023
DiffuDetox: A Mixed Diffusion Model for Text Detoxification
Text detoxification is a conditional text generation task aiming to remo...
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06/09/2023
Bayesian Knowledge-driven Critiquing with Indirect Evidence
Conversational recommender systems (CRS) enhance the expressivity and pe...
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05/30/2023
Revisiting Random Forests in a Comparative Evaluation of Graph Convolutional Neural Network Variants for Traffic Prediction
Traffic prediction is a spatiotemporal predictive task that plays an ess...
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05/29/2023
Perimeter Control Using Deep Reinforcement Learning: A Model-free Approach towards Homogeneous Flow Rate Optimization
Perimeter control maintains high traffic efficiency within protected reg...
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05/26/2023
LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations
Can a Large Language Model (LLM) solve simple abstract reasoning problem...
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05/07/2023
A Generalized Framework for Predictive Clustering and Optimization
Clustering is a powerful and extensively used data science tool. While c...
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04/23/2023
LogicRec: Recommendation with Users' Logical Requirements
Users may demand recommendations with highly personalized requirements i...
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04/06/2023
Safe MDP Planning by Learning Temporal Patterns of Undesirable Trajectories and Averting Negative Side Effects
In safe MDP planning, a cost function based on the current state and act...
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11/26/2022
A Critical Review of Traffic Signal Control and A Novel Unified View of Reinforcement Learning and Model Predictive Control Approaches for Adaptive Traffic Signal Control
Recent years have witnessed substantial growth in adaptive traffic signa...
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11/11/2022
pyRDDLGym: From RDDL to Gym Environments
We present pyRDDLGym, a Python framework for auto-generation of OpenAI G...
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11/08/2022
Learning to Follow Instructions in Text-Based Games
Text-based games present a unique class of sequential decision making pr...
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10/18/2022
Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus
The Abstraction and Reasoning Corpus (ARC) aims at benchmarking the perf...
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03/23/2022
Sample-efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs
Recent advances in deep learning have enabled optimization of deep react...
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03/14/2022
TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation
Weakly supervised semantic segmentation (WSSS) with only image-level sup...
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01/17/2022
Unintended Bias in Language Model-driven Conversational Recommendation
Conversational Recommendation Systems (CRSs) have recently started to le...
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11/28/2021
ExCon: Explanation-driven Supervised Contrastive Learning for Image Classification
Contrastive learning has led to substantial improvements in the quality ...
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10/05/2021
Multi-axis Attentive Prediction for Sparse EventData: An Application to Crime Prediction
Spatiotemporal prediction of event data is a challenging task with a lon...
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08/02/2021
Planning with Learned Binarized Neural Networks Benchmarks for MaxSAT Evaluation 2021
This document provides a brief introduction to learned automated plannin...
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06/14/2021
RAPTOR: End-to-end Risk-Aware MDP Planning and Policy Learning by Backpropagation
Planning provides a framework for optimizing sequential decisions in com...
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05/29/2021
EDDA: Explanation-driven Data Augmentation to Improve Model and Explanation Alignment
Recent years have seen the introduction of a range of methods for post-h...
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03/22/2021
Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning
Online class-incremental continual learning (CL) studies the problem of ...
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01/25/2021
Online Continual Learning in Image Classification: An Empirical Survey
Online continual learning for image classification studies the problem o...
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10/24/2020
Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering
Most existing One-Class Collaborative Filtering (OC-CF) algorithms estim...
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08/31/2020
Adversarial Shapley Value Experience Replay for Task-Free Continual Learning
Continual learning is a branch of deep learning that seeks to strike a b...
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08/03/2020
Noise Contrastive Estimation for Autoencoding-based One-Class Collaborative Filtering
One-class collaborative filtering (OC-CF) is a common class of recommend...
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07/11/2020
Batch-level Experience Replay with Review for Continual Learning
Continual learning is a branch of deep learning that seeks to strike a b...
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07/02/2020
ε-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning
Resolving the exploration-exploitation trade-off remains a fundamental p...
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06/10/2020
Bayesian Experience Reuse for Learning from Multiple Demonstrators
Learning from demonstrations (LfD) improves the exploration efficiency o...
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02/29/2020
Contextual Policy Reuse using Deep Mixture Models
Reinforcement learning methods that consider the context, or current sta...
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04/23/2019
Optimizing Search API Queries for Twitter Topic Classifiers Using a Maximum Set Coverage Approach
Twitter has grown to become an important platform to access immediate in...
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04/19/2019
Reward Potentials for Planning with Learned Neural Network Transition Models
Optimal planning with respect to learned neural network (NN) models in c...
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04/05/2019
Scalable Nonlinear Planning with Deep Neural Network Learned Transition Models
In many real-world planning problems with factored, mixed discrete and c...
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11/26/2018
Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models
In this paper, we leverage the efficiency of Binarized Neural Networks (...
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11/26/2018
Planning with Learned Binarized Neural Network Transition Models in Factored State and Action Spaces
In this paper, we leverage the efficiency of Binarized Neural Networks (...
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11/02/2018
Noise Contrastive Estimation for Scalable Linear Models for One-Class Collaborative Filtering
Previous highly scalable one-class collaborative filtering methods such ...
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08/31/2018
Aesthetic Features for Personalized Photo Recommendation
Many photography websites such as Flickr, 500px, Unsplash, and Adobe Beh...
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05/20/2018
Conditional Inference in Pre-trained Variational Autoencoders via Cross-coding
Variational Autoencoders (VAEs) are a popular generative model, but one ...
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01/04/2017
Stochastic Planning and Lifted Inference
Lifted probabilistic inference (Poole, 2003) and symbolic dynamic progra...
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07/04/2012
Approximate Linear Programming for First-order MDPs
We introduce a new approximate solution technique for first-order Markov...
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02/14/2012
