Downtown New Orleans, Louisiana and the Missisippi River
NeurIPS 2023
December 10 - 16, 2023
New Orleans, Louisiana

Overview

The Neural Information Processing Systems (NeurIPS) annual meeting fosters the exchange of research on neural information processing systems in their biological, technological, mathematical, and theoretical aspects. The core focus is peer-reviewed novel research which is presented and discussed in the general session, along with invited talks by leaders in their fields.

Amazon organizing committee members

Accepted publications

Workshops

NeurIPS 2023 Workshop on AutoML at Your Fingertips
December 10
In this workshop, we introduce AutoGluon, a state-of-the-art and easy-to-use toolkit that empowers multimodal AutoML. Different from most AutoML systems that focus on solving tabular tasks containing categorical and numerical features, we consider supervised learning tasks on various types of data including tabular features, text, image, time series, as well as their combinations. We will introduce the real-world problems that AutoGluon can help you solve within three lines of code and the fundamental techniques adopted in the toolkit. Rather than diving deep into the mechanisms underlining each individual ML models, we emphasize on how you can take advantage of a diverse collection of models to build an automated ML pipeline. Our workshop will also emphasize on the techniques behind automatically building and training deep learning models, which are powerful yet cumbersome to manage manually.

Organizers: Nick Erickson, Tony Hu, Zhiqiang Tang

Website: https://autogluon.github.io/neurips-autogluon-workshop
NeurIPS 2023 Workshop on LatinX in AI
December 11
The workshop is a one-day event with invited speakers, oral presentations, and posters. The event brings together faculty, graduate students, research scientists, and engineers for an opportunity to connect and exchange ideas. There will be a panel discussion and a mentoring session to discuss current research trends and career choices in Artificial Intelligence and Machine Learning. While all presenters will identify primarily as LatinX, all are invited to attend.

Amazon organizer: Brayan Valdés Ortiz

Website: https://www.latinxinai.org/neurips-2023
NeurIPS 2023 Large Language Model Efficiency Challenge:1 LLM + 1GPU + 1Day
December 15
Our goal is to democratize access to language models and address three major issues: (1) Lack of transparency around model training methods leads to a majority of models being not reproducible. (2) The absence of a standard benchmark to evaluate these models side-by-side. (3) Insufficient access to dedicated hardware prevents widespread availability and usage of these models.

Here we present a LLM efficiency challenge, to tackle these three challenges and democratize access to state of the art LLMs.

Website: https://llm-efficiency-challenge.github.io
NeurIPS 2023 Workshop on Table Representation Learning
December 15
The Table Representation Learning (TRL) workshop is the first in this emerging research area and concentrates on three main goals: motivate tables as a primary modality for representation and generative learning and advance the area further, Showcase impactful applications of pretrained table models and discussing future opportunities, and foster discussion and collaboration across the ML, NLP and DB communities.

Website: https://table-representation-learning.github.io
NeurIPS 2023 Workshop on Distribution Shifts (DistShifts)
December 15
NeurIPS 2023 Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response (AI + HADR)
December 15
Humanitarian crises from disease outbreak to war to oppression against disadvantaged groups have threatened people and their communities throughout history. Natural disasters are a single, extreme example of such crises. In the wake of hurricanes, earthquakes, and other such crises, people have ceaselessly sought ways--often harnessing innovation--to provide assistance to victims after disasters have struck.

Through this workshop, we intend to establish meaningful dialogue between the Artificial Intelligence (AI) and Humanitarian Assistance and Disaster Response (HADR) communities. By the end of the workshop, the ICCV research community can learn the practical challenges of aiding those in crisis, while the HADR community can get to know the state of art and practice in AI. We seek to establish a pipeline of transitioning the research created by the AI and Computer Vision community to real-world humanitarian issues. We believe such an endeavor is possible due to recent successes in applying techniques from various AI and Machine Learning (ML) disciplines to HADR.

Website: https://www.hadr.ai
Natasha Krell, Will Gleave, Daniel Nakada, Justin Downes, Amanda Willet, Matthew Baran
2023
NeurIPS 2023 Workshop on Robustness of Zero/Few-shot Learning in Foundation Models (R0-FoMo)
December 15
The goal of this workshop is to bring together machine learning researchers from academia and industry to encourage knowledge transfer and collaboration on these topics to discover ideas that can expand our understanding of robustness of few-shot learning approaches based on large foundational models. The ideal outcome of the workshop is to identify a set of concrete research directions to enable the next generation of robust models that are safe and responsible.

Website: https://sites.google.com/view/r0-fomo
NeurIPS 2023 Workshop on Deep Generative Models for Health
December 15
In this workshop, we provide a unique venue for the most recent trends in research on deep generative models, focusing on exploring their potential for health applications. We also provide the optimal setting to discuss the open problems that prevent these methods from having a profound positive impact in clinical settings. This workshop will be the ideal venue to attract a diverse pool of researchers aiming to integrate generative models in health scenarios.

Website: https://neurips.cc/virtual/2023/workshop/66495
NeurIPS 2023 Workshop on Efficient Natural Language and Speech Processing (ENLSP)
December 16
The third version of the Efficient Natural Language and Speech Processing (ENLSP-III) workshop will focus on the future of large language models and their emerging applications on different domains such as natural language, speech processing, and biological sequences; and the target is on how to make them more efficient in terms of Data, Model, Training, and Inference for real-world applications as well as academic research. The workshop program offers an interactive platform for gathering different experts and talents from academia and industry through invited talks, panel discussion, paper submissions, reviews, interactive posters, oral presentations and a mentorship program. This will be a unique opportunity to discuss and share challenging problems, build connections, exchange ideas and brainstorm solutions, and foster future collaborations. The topics of this workshop can be of interest for people working on general machine learning, deep learning, optimization, theory and NLP & Speech applications.

Website: https://neurips2023-enlsp.github.io
NeurIPS 2023 Workshop on Robot Learning
December 16
In the 6th iteration of the Robot Learning workshop at NeurIPS, we will create a space for researchers from diverse backgrounds to gather and discuss the opportunities, challenges, and risks associated with large models in robotics research. Robotics is one of the most exciting and diverse applications for machine learning. It is both a hard challenge and a fruitful source of problems for machine learning approaches and our workshop is a space for members of both communities to meet.

Website: https://www.robot-learning.ml/2023
NeurIPS 2023 Workshop on SyntheticData4ML
December 16
NeurIPS 2023 Workshop on Federated Learning in the Age of Foundation Models
December 16
NeurIPS 2023 Workshop on I Can’t Believe It’s Not Better (ICBINB): Failure Modes in the Age of Foundation Models
December 16
NeurIPS 2023 Workshop on Machine Learning for Structural Biology
December 15
NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in the Real World
December 16, 8:00 AM - 3:30 PM EST
This workshop aims to bring together researchers from academia and industry to discuss major challenges, outline recent advances, and highlight future directions pertaining to novel and existing real-world experimental design and active learning problems. In addition, we aim to highlight new and emerging research opportunities for the machine learning community that arise from the evolving needs to make experimental design and active learning procedures that are theoretically and practically relevant for practical applications. Examples include protein design, causal discovery, drug design, and materials design, to name a few.

Website: https://realworldml.github.io/neurips2023/
NeurIPS 2023 Workshop on Efficient Natural Language and Speech Processing (ENLSP-III)
December 16
The third version of the Efficient Natural Language and Speech Processing (ENLSP-III) workshop will focus on the future of large language models and their emerging applications on different domains such as natural language, speech processing, and biological sequences; and the target is on how to make them more efficient in terms of Data, Model, Training, and Inference for real-world applications as well as academic research.

https://neurips2023-enlsp.github.io/
NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following
December 15
NeurIPS 2023 Workshop on Optimization for Machine Learning (OPT2023)
December 15
NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning
December 16
Many in the ML community wish to take action on climate change, but are unsure of the pathways through which they can have the most impact. This workshop highlights work that demonstrates that, while no silver bullet, ML can be an invaluable tool in reducing greenhouse gas emissions and in helping society adapt to the effects of climate change. Climate change is a complex problem, for which action takes many forms - from theoretical advances to deployment of new technology. Many of these actions represent high-impact opportunities for real-world change, and are simultaneously interesting academic research problems.

Website: https://www.climatechange.ai/events/neurips2023
ES, M, Madrid
Amazon's International Technology org in EU (EU INTech) is creating new ways for Amazon customers discovering Amazon catalog through new and innovative Customer experiences. Our vision is to provide the most relevant content and CX for their shopping mission. We are responsible for building the software and machine learning models to surface high quality and relevant content to the Amazon customers worldwide across the site. The team, mainly located in Madrid Technical Hub, London and Luxembourg, comprises Software Developer and ML Engineers, Applied Scientists, Product Managers, Technical Product Managers and UX Designers who are experts on several areas of ranking, computer vision, recommendations systems, Search as well as CX. Are you interested on how the experiences that fuel Catalog and Search are built to scale to customers WW? Are interesting on how we use state of the art AI to generate and provide the most relevant content? Key job responsibilities We are looking for Applied Scientists who are passionate to solve highly ambiguous and challenging problems at global scale. You will be responsible for major science challenges for our team, including working with text to image and image to text state of the art models to scale to enable new Customer Experiences WW. You will design, develop, deliver and support a variety of models in collaboration with a variety of roles and partner teams around the world. You will influence scientific direction and best practices and maintain quality on team deliverables. We are open to hiring candidates to work out of one of the following locations: Madrid, M, ESP
US, WA, Bellevue
Imagine being part of an agile team where your ideas have the potential to reach millions of customers. Picture working on cutting-edge, customer-facing solutions, where every team member is a critical voice in the decision making process. Envision being able to leverage the resources of a Fortune 500 company within the atmosphere of a start-up. Welcome to Amazon’s NCRC team. We solve complex problems in an ambiguous space, focusing on reducing return costs and improving the customer experience. We build solutions that are distributed on a large scale, positively impacting experiences for our customers and sellers. Come innovate with the NCRC team! The Net Cost of Refunds and Concessions (NCRC) team is looking for a Senior Manager Data Science to lead a team of economists, business intelligence engineers and business analysts who investigate business problems, develop insights and build models & algorithms that predict and quantify new opportunity. The team instigates and productionalizes nascent solutions around four pillars: outbound defects, inbound defects, yield optimization and returns reduction. These four pillars interact, resulting in impacts to our overall return rate, associated costs, and customer satisfaction. You may have seen some downstream impacts of our work including Amazon.com customer satisfaction badges on the website and app, new returns drop off optionality, and faster refunds for low cost items. In this role, you will set the science vision and direction for the team, collaborating with internal stakeholders across our returns and re-commerce teams to scale and advance science solutions. This role is based in Bellevue, WA Key job responsibilities * Single threaded leader responsible for setting and driving science strategy for the organization. * Lead and provide coaching to a team of Scientists, Economists, Business Intelligence Engineers and Business Analysts. * Partner with Engineering, Product and Machine Learning leaders to deliver insights and recommendations across NCRC initiatives. * Lead research and development of models and science products powering return cost reduction. * Educate and evangelize across internal teams on analytics, insights and measurement by writing whitepapers, knowledge documentation and delivering learning sessions. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
US, WA, Bellevue
We are designing the future. If you are in quest of an iterative fast-paced environment, where you can drive innovation through scientific inquiry, and provide tangible benefit to hundreds of thousands of our associates worldwide, this is your opportunity. Come work on the Amazon Worldwide Fulfillment Design & Engineering Team! We are looking for an experienced and Research Scientist with background in Ergonomics and Industrial Human Factors, someone that is excited to work on complex real-world challenges for which a comprehensive scientific approach is necessary to drive solutions. Your investigations will define human factor / ergonomic thresholds resulting in design and implementation of safe and efficient workspaces and processes for our associates. Your role will entail assessment and design of manual material handling tasks throughout the entire Amazon network. You will identify fundamental questions pertaining to the human capabilities and tolerances in a myriad of work environments, and will initiate and lead studies that will drive decision making on an extreme scale. .You will provide definitive human factors/ ergonomics input and participate in design with every single design group in our network, including Amazon Robotics, Engineering R&D, and Operations Engineering. You will work closely with our Worldwide Health and Safety organization to gain feedback on designs and work tenaciously to continuously improve our associate’s experience. Key job responsibilities - Collaborating and designing work processes and workspaces that adhere to human factors / ergonomics standards worldwide. - Producing comprehensive and assessments of workstations and processes covering biomechanical, physiological, and psychophysical demands. - Effectively communicate your design rationale to multiple engineering and operations entities. - Identifying gaps in current human factors standards and guidelines, and lead comprehensive studies to redefine “industry best practices” based on solid scientific foundations. - Continuously strive to gain in-depth knowledge of your profession, as well as branch out to learn about intersecting fields, such as robotics and mechatronics. - Travelling to our various sites to perform thorough assessments and gain in-depth operational feedback, approximately 25%-50% of the time. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
US, NY, New York
Amazon Advertising exists at the intersection of marketing and e-commerce and offers advertisers a rich array of innovative advertising solutions across Amazon-owned and third party properties. We believe that advertising, when done well, can greatly enhance the value of the customer experience and generate a positive return on investment for our advertising partners. We are currently looking for a highly skilled and motivated Data Scientist to help scale our growing advertising business. The Data Scientist is a key member of the Global Marketing Insights team at Amazon Ads, working with marketing, product, retail and other Amazon business partners to analyze and improve advertisers’ performance on Amazon, in support of their marketing objectives. You will work with Amazon's unique data and translate it into high-quality and actionable insights and recommendations to improve the effectiveness of advertiser campaigns and unlock business opportunities. Day to day activities include analyzing advertiser behaviors to develop data-driven insights on what tactics and strategies lead to success. You will also build automated solutions to generate science driven insights at scale, that are distributed to our advertisers across channels. Basic qualifications - Bachelor's or Master's degree in Engineering, Statistics, Economics, or a related technical field - Proven experience in data analytics or data science roles - Proficiency with SQL and Python - Strong understanding of basic statistical techniques and methodologies such as distributions, hypothesis testing, regressions, experimentation, A/B Testing etc. - Excellent organizational, interpersonal, and communication skills (both written and verbal) - Ability to work cross-functionally and with technical and non-technical stakeholders Preferred qualifications - Understanding of advanced statistical techniques and methodologies such as causal inference, propensity score matching, machine learning etc. - Experience with developing and deploying production machine learning models, especially on cloud platforms - Experience building and managing data pipelines - Experience with digital advertising products, performance analytics , marketing and advertising campaigns - MBA, Master’s, or Doctoral degree in Economics, Engineering, Marketing, Statistics, Advertising, or related fields - Publication track record/writing experience (ex. published a paper in a technical journal or trade publication) About the team The Marketing Insights team is responsible for delivering science backed insights to millions of advertisers via our marketing messages. Our team is distributed across the globe and is building cutting edge data science to identify and communicate the impact of various advertising strategies for our products. We are open to hiring candidates to work out of one of the following locations: New York, NY, USA
US, WA, Seattle
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Python is necessary, and experience with SQL and Scala would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com. We are open to hiring candidates to work out of one of the following locations: Chicago, IL, USA | Seattle, WA, USA | Washington, DC, USA
US, WA, Seattle
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Python is necessary, and experience with SQL and Scala would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com. We are open to hiring candidates to work out of one of the following locations: Chicago, IL, USA | Seattle, WA, USA | Washington, DC, USA
US, WA, Seattle
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Python is necessary, and experience with SQL and Scala would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com. We are open to hiring candidates to work out of one of the following locations: Chicago, IL, USA | Seattle, WA, USA | Washington, DC, USA
US, CA, Santa Clara
Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations. The Generative AI team helps AWS customers accelerate the use of Generative AI to solve business and operational challenges and promote innovation in their organization. As an applied scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for talented scientists capable of applying ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others. AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. Key job responsibilities The primary responsibilities of this role are to: Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across industries Interact with customer directly to understand their business problems, and help them with defining and implementing scalable Generative AI solutions to solve them Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new solutions About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. We are open to hiring candidates to work out of one of the following locations: San Francisco, CA, USA | Santa Clara, CA, USA
US, WA, Bellevue
Amazon.com Services, Inc. is looking for a motivated individual with strong analytical skills and practical experience to join our Modeling and Optimization team. We are hiring specialists into our scientific team with expertise in network and combinatorial optimization, simulation-based design, and/or control theory. Amazon is growing rapidly and because we are driven by faster delivery to customers, a more efficient supply chain network, and lower cost of operations, our main focus is in the development of analytical strategic models and automation tools fed by massive amounts of data. You will be responsible for building these models/tools that improve the economics of Amazon’s worldwide fulfillment networks in North America, Europe, and Japan, China, and India as Amazon increases the speed and decreases the cost to deliver products to customers. You will identify and evaluate opportunities to reduce variable costs by improving fulfillment center processes, transportation operations and scheduling, and the execution to operational plans. You will also improve the efficiency of capital investment by helping the fulfillment centers to improve storage utilization and the effective use of automation. Finally, you will help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools. The ideal candidate will have good communication skills with both technical and business people with ability to speak at a level appropriate for the audience. Key job responsibilities * Understand ambiguous business problems, model it in the simplest and most effective manner with limited guidance. * Use new or existing tools to support internal partner-teams and provide the best, science-based guidance. * Contribute to existing tools with highly disciplined coding practices. * Contribute to the growth of knowledge of our team and the scientific community with internal and external publications or presentations. About the team * At the Modeling and Optimization (MOP) team, we use optimization, algorithm design, statistics, and machine learning to improve decision-making capabilities across WW Operations and Amazon Logistics. * We focus on transportation topology, labor and resource planning, routing science, visualization research, data science and development, and process optimization. * We create models to simulate, optimize, and control the fulfillment network with the objective of reducing cost while improving speed and reliability. * We support multiple business line, therefore maintain a comprehensive and objective view, coordinating solutions across organizational lines where possible. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
US, CA, Santa Clara
Amazon AI is looking for world class scientists and engineers to join its AWS AI. This group is entrusted with developing core natural language processing, generative AI, deep learning and machine learning algorithms for AWS. You will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore conceptually new solutions. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. A day in the life Inclusive Team Culture Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life Balance Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. About the team The Amazon Web Services (AWS) Next Gen DevX (NGDE) team uses generative AI and foundation models to reimagine the experience of all builders on AWS. From the IDE to web-based tools and services, AI will help engineers work on large and small applications. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world. If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you. We are open to hiring candidates to work out of one of the following locations: Santa Clara, CA, USA