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We are pleased to welcome you to the 2023 ACM Workshop on Artificial Intelligence for Performance Modeling, Prediction, and Control - AIPerf'23.
In its first edition, AIPerf intends to foster the usage of AI (such as probabilistic methods, machine ...
We demonstrate how state-of-art open-source tools for automatic speech recognition (vosk) and dialogue management (rasa) can be integrated on a social robotic platform (PAL Robotics' ARI robot) to provide rich verbal interactions.
Our open-source, ROS-...
Adaptation and personalization are critical elements when modeling robot behaviors toward users in real-world settings. Multiple aspects of the user need to be taken into consideration in order to personalize the interaction, such as their personality, ...
This research examines a two-player combinatorial game, Game of Thrones: Hand of the King, and applies several different techniques to develop an effective AI player for this game. We used several approaches including simple game state analysis, ...
Deep learning (DL) is a prominent and growing area of machine learning that is rapidly changing how complex data in the world is modeled, interpreted, and utilized. To model these complexities, building accurate and robust DL models can often require ...
Many research areas rely on the ability to observe insect position and pose through markerless tracking. Neural networks provide more robust tracking systems than traditional computer vision-based systems. However, they require many human-hours to label ...
This workshop will teach instructors how to incorporate Machine Learning into their mobile course using ML Kit for Firebase. ML Kit provides powerful machine learning functionality to your app running either iOS or Android and is for both experienced ...
Pretrained large language models (LLMs) have consistently shown state-of-the-art performance across multiple natural language processing (NLP) tasks. These models are of much interest for a variety of industrial applications that use NLP as a core ...
We propose to accelerate use-inspired basic research in causal AI through a suite of causal tools and libraries that simultaneously provides core causal AI functionality to practitioners and creates a platform for research advances to be rapidly ...
Commercially sold electrical or gas products must comply with the safety standards imposed within a country and get registered and certified by a regulated body. However, with the increasing transition of businesses to e-commerce platforms, it becomes ...
Online marketplaces are able to offer a staggering array of products that no physical store can match. While this makes it more likely for customers to find what they want, in order for online providers to ensure a smooth and efficient user experience, ...
NLU models power several user facing experiences such as conversations agents and chat bots. Building NLU models typically consist of 3 stages: a) building or finetuning a pre-trained model b) distilling or fine-tuning the pre-trained model to build ...
With the rapidly growing AI market opportunities and the accelerated adoption of AI technologies for a wide range of real-world applications, responsible AI has attracted increasing attention in both academia and industries. In this talk, I will focus ...
Understanding student behavior patterns is fundamental to building smart campuses. However, the diversity of student behavior and the complexity of educational data not only bring great obstacles to the relevant research, but also leads to unstable ...
Hate speech is a challenging problem in today's online social media. One of the current solutions followed by different social media platforms is detecting hate speech using human-in-the-loop approaches. After detection, they moderate such hate speech ...
Graph neural networks (GNNs), which extend deep learning models to graph-structured data, have achieved great success in many applications such as detecting malicious activities. However, GNN-based models are vulnerable to camouflage behavior of ...
Graphs are ubiquitous, which makes machine learning on graphs an important research area. While there are many aspects to this field, our research is focused primarily on two aspects of it. The first research question concerns privacy in graphs, where ...
Hateful content is a growing concern across different platforms, whether it is a moderated platform or an unmoderated platform. The public expression of hate speech encourages the devaluation of minority members. It has some consequences in the real ...
A knowledge graph (KG) consists of numerous triples, in which each triple, i.e., (head entity, relation, tail entity), denotes a real-world assertion. Many large-scale KGs have been developed, e.g., general-purpose KGs Freebase and YAGO. Also, lots of ...
Psychedelic Forms is a series of case studies that explore deep learning (DL) possibilities for creating a tangible form guided by text prompt and 3D object. The selected generated digital 3D objects were manually altered and prepared for 3D printing ...