Infinia ML Team Publishes Six Papers at 2019 International Conference on Machine Learning

Chief Scientist Larry Carin and Data Scientist Jun Liu


DURHAM, N.C., June 10, 2019  — Infinia ML, an advanced machine learning company, announced today that members of its data science team collectively published six papers at the Thirty-sixth International Conference on Machine Learning, which takes place this week in Long Beach, California.

ICML, which attracts research from institutions like Google, Stanford, Microsoft, MIT, and Facebook, is widely considered one of the world’s most prestigious machine learning gatherings. This year the conference accepted 774 papers, just 22.6% of the total submitted.

“Having three members of the Infinia ML team contribute six papers to ICML sets us apart from others of our size and stage,” said Infinia ML CEO Robbie Allen. “The accomplishments of our data scientists at ICML further prove that we can address the most advanced data challenges.”

Infinia ML Chief Scientist Larry Carin, one of the world’s most widely published machine learning researchers, is a co-author on five papers, covering topics from reinforcement learning to generative adversarial networks. Infinia ML Research Scientist Hongteng Xu is the lead author on a paper about a joint learning framework for graph matching and node embedding problems, which Carin also co-authored. Infinia ML Data Scientist Jun Liu co-authored a sixth paper on non-negative matrix factorization, a tool widely used in machine learning and data mining.

“We’re continuing to build an academic foundation that will help move the business world forward,” said Carin. “The best part is that the application of machine learning to business is just getting started.”

Research Scientist Hongteng Xu

About Infinia ML

Infinia ML provides the people, process, and technology to automate business challenges with data science. Serving industries from manufacturing and healthcare to marketing and human resources, the company’s capabilities include natural language processing, object detection, and behavior prediction.

The Durham, N.C. company is led by Chief Executive Officer Robbie Allen, an experienced AI entrepreneur; Chief Scientist Lawrence Carin, Ph.D., one of the world’s most published machine learning experts; and Duke University’s Vice Provost for Research and Executive Chairman and Carrick Capital Partners Managing Director Mike Salvino. Together, the Infinia ML team has 31 patents, 11 books, 10 Ph.D.s and more than 600 published papers. Learn more at

Infinia ML Increases Research Contributions to NeurIPS, the World’s Top Machine Learning Conference

Infinia ML Chief Scientist Larry Carin Raises NeurIPS/NIPS Research Contributions to 44 Papers Since 2004

Infinia ML Research Scientist Hongteng Xu.


MONTREAL, December 3, 2018 – Infinia ML, an advanced machine learning company that delivers transformative automation solutions and data science to enterprise businesses, is celebrating more accepted research papers at the world’s most prestigious machine learning conference.

The Conference on Neural Information Processing Systems (NeurIPS, formerly NIPS), which has been compared to the AI world’s version of SXSW and CES, accepted less than 21% of submitted papers in 2018.

Among the accepted works is a paper co-authored by Infinia ML Research Scientist Hongteng Xu. “Distilled Wasserstein Learning for Word Embedding and Topic Modeling” proposes a machine learning method for hospital patient admission records that could help predict mortality and recommend procedures.

Dr. Xu and his colleagues are conference veterans. Infinia ML Chief Scientist Larry Carin co-authored three papers at NeurIPS this year, including Xu’s. In 2017 he was the event’s most-published researcher with ten papers. Altogether, Dr. Carin has contributed 44 papers to the conference since 2004. Infinia ML Data Scientist Ricardo Henao has contributed eleven since 2009.

This year’s NeurIPS conference is in Montreal through Saturday December 8th, 2018.

Infinia ML Research Accepted at NIPS 2018

September 10, 2018 — Infinia ML is focused on business impact, but our commitment to academic research keeps us on the cutting edge of machine learning.

That’s why we’re proud to announce that the work of our Research Scientist Hongteng Xu, Ph.D., was among the ~22% of papers accepted at the upcoming Conference on Neural Information Processing System (NIPS), which Quartz has called “the world’s biggest and most important AI conference.”


Infinia ML’s First Published Papers

When Dr. Hongteng Xu joined our team, we announced that he would “continue his academic research inside Infinia ML, developing the intellectual foundation for advanced business solutions.”

Now, we’re pleased to share that Dr. Xu has already begun rolling out his research, and his work has been accepted by two prestigious conferences taking place this spring.

Benefits from Superposed Hawkes Processes” will appear at the 21st International Conference on Artificial Intelligence and Statistics (AISTATS). The gathering is one of the top machine learning conferences, with a paper acceptance rate of just 33%.

Dr. Hongteng Xu
Hongteng Xu, Ph.D.

Dr. Xu and his co-authors, who include Infinia ML Chief Scientist Larry Carin, Ph.D., showed the potential to solve the “cold start” problem for recommendation systems. In other words, it may help the kind of systems that suggest products, movies, or music make better recommendations for new users haven’t given the system much data to work with.

Another of Xu’s papers, “Learning an Inverse Tone Mapping Network with a Generative Adversarial Regularizer,” has been accepted by the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), a top signal processing conference.

In this paper, Xu and his collaborators proposed a new deep learning technique for inverse tone mapping, a process which helps digital images achieve better visual quality. Their innovation beats the state-of the-art tone mapping methods.

Congratulations Dr. Xu – we’re proud to have you on our team, and we look forward to sharing more of your research with the world!