The Conference and Workshop on Neural Information Processing Systems is a machine learning and computational neuroscience conference held every December. The conference is currently a double-track meeting that includes invited talks as well as oral and poster presentations of refereed papers, followed by parallel-track workshops that up to 2013 were held at ski resorts.
The AAAI Conference on Artificial Intelligence (AAAI) is one of the leading international academic conference in artificial intelligence held annually. Along with ICML, NeurIPS and ICLR, it is one of the primary conferences of high impact in machine learning and artificial intelligence research. It is supported by the Association for the Advancement of Artificial Intelligence. Precise dates vary from year to year, but paper submissions are generally due at the end of August to beginning of September, and the conference is generally held during the following February. The first AAAI was held in 1980 at Stanford University, Stanford California.
Empirical Methods in Natural Language Processing (EMNLP) is a leading conference in the area of natural language processing and artificial intelligence. Along with the Association for Computational Linguistics (ACL), it is one of the two primary high impact conferences for natural language processing research. EMNLP is organized by the ACL special interest group on linguistic data (SIGDAT) and was started in 1996, based on an earlier conference series called Workshop on Very Large Corpora (WVLC).
Raquel Urtasun is a professor at the University of Toronto. Urtasun uses artificial intelligence, particularly deep learning, to make vehicles and other machines perceive the world more accurately and efficiently.
Yee-Whye Teh is a professor of statistical machine learning in the Department of Statistics, University of Oxford. Prior to 2012 he was a reader at the Gatsby Charitable Foundation computational neuroscience unit at University College London. His work is primarily in machine learning, artificial intelligence, statistics and computer science.
The International Conference on Learning Representations (ICLR) is a machine learning conference typically held in late April or early May each year. The conference includes invited talks as well as oral and poster presentations of refereed papers. Since its inception in 2013, ICLR has employed an open peer review process to referee paper submissions. In 2019, there were 1591 paper submissions, of which 500 accepted with poster presentations (31%) and 24 with oral presentations (1.5%).. In 2021, there were 2997 paper submissions, of which 860 were accepted (29%)..
Deep reinforcement learning is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem of a computational agent learning to make decisions by trial and error. Deep RL incorporates deep learning into the solution, allowing agents to make decisions from unstructured input data without manual engineering of the state space. Deep RL algorithms are able to take in very large inputs and decide what actions to perform to optimize an objective. Deep reinforcement learning has been used for a diverse set of applications including but not limited to robotics, video games, natural language processing, computer vision, education, transportation, finance and healthcare.
Multi-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that coexist in a shared environment. Each agent is motivated by its own rewards, and does actions to advance its own interests; in some environments these interests are opposed to the interests of other agents, resulting in complex group dynamics.
The European Laboratory for Learning and Intelligent Systems (ELLIS) is a pan-European nonprofit organization for the promotion of artificial intelligence with a focus on machine learning. The organization's goal is to establish top AI research institutes, strengthen basic research and create a European PhD programme for AI.
Sanja Fidler is an associate professor at the University of Toronto and Director of AI at Nvidia. She is also a co-founder of the Vector Institute, University of Toronto and Canada CIFAR AI Chair. Her research is in the areas of computer vision and artificial intelligence.
Maria-Florina (Nina) Balcan is a Romanian-American computer scientist whose research investigates machine learning, algorithmic game theory, theoretical computer science, including active learning, kernel methods, random-sampling mechanisms and envy-free pricing. She is an associate professor of computer science at Carnegie Mellon University.
Isabelle Guyon is a French-born researcher in machine learning known for her work on support-vector machines, artificial neural networks and bioinformatics. She is a Chair Professor at the University of Paris-Saclay.
Adji Bousso Dieng is a Senegalese Computer Scientist and Statistician working in the field of Artificial Intelligence. Her research bridges probabilistic graphical models and deep learning to discover meaningful structure from unlabelled data. She is currently an Artificial Intelligence Research Scientist at Google Brain in Mountain View, California. In 2021, she will start her tenure-track faculty position at Princeton University becoming the first Black female faculty member in the School of Engineering and Applied Science as well as the first Black faculty member ever in the Department of Computer Science. Dieng recently founded the non-profit “The Africa I Know” (TAIK) with the goal to inspire young Africans to pursue careers in STEM and AI by showcasing African role models, informing the general public about developments in STEM and AI by Africans, and educating the general public about the rich history of Africa.
Black in AI, formally called the Black in AI Workshop, is a technology research organization and affinity group, founded by computer scientists Timnit Gebru and Rediet Abebe in 2017. It started as a conference workshop, later pivoting into an organization. Black in AI increases the presence and inclusion of Black people in the field of artificial intelligence (AI) by creating space for sharing ideas, fostering collaborations, mentorship, and advocacy.
Samy Bengio is a Canadian computer scientist, Senior Director of AI and Machine Learning Research at Apple, and a former long-time scientist at Google known for leading a large group of researchers working in machine learning including adversarial settings. Bengio left Google shortly after the company fired his report, Timnit Gebru, without first notifying him. At the time, Bengio said that he had been "stunned" by what happened to Gebru. He is also among the three authors who developed Torch in 2002, the ancestor of PyTorch, one of today's two largest machine learning frameworks.
Marius Lindauer is a German computer scientist and professor of machine learning at the institute of artificial intelligence of the Leibniz University Hannover. He is known for his research on Automated Machine Learning and other meta-algorithmic approaches.
François Chollet is a French software engineer and artificial intelligence researcher currently working at Google. Chollet is the creator of the Keras deep-learning library, released in 2015, and a main contributor to the TensorFlow machine learning framework. His research focuses on computer vision, the application of machine learning to formal reasoning, abstraction, and how to achieve greater generality in artificial intelligence.
Meta AI is an artificial intelligence laboratory that belongs to Meta Platforms Inc. Meta AI intends to develop various forms of artificial intelligence, improving augmented and artificial reality technologies. Meta AI is an academic research laboratory focused on generating knowledge for the AI community. This is in contrast to Facebook's Applied Machine Learning (AML) team, which focuses on practical applications of its products.
Mi Zhang is a computer scientist at Ohio State University, where he is an Associate Professor of Computer Science and Engineering and the director of AIoT and Machine Learning Systems Lab. He is best known for his work in Edge AI, Artificial Intelligence of Things (AIoT), machine learning systems, and mobile health.
