Mementor Beta
The Mementor portal should help us scheduling spontaneous virtual mentor sessions during ICLR and beyond. Our goal is to enable mentorship opportunities for researchers in machine learning, both as mentors and mentees, with a special focus on under-represented minorities.
Our initial goal is to provide a platform to support conversations between mentors and mentees. The mode of operation initially will be a “lighter” version, where a mentor, at a time of their convenience, has a video call, which everybody willing as a mentee can join. No person-to-person commitment.
The mentorship session serves as a platform to share experiences. These could be technical and research related (e.g., research topics and technical discussions), or could be about scientific communication (e.g., paper writing, presentation, networking), or could also be mental health, burnouts, work ethics, PhD life etc. The goal is to facilitate sharing of experiences between members of the community which would not happen otherwise.
Note: The mentorship sessions are not a platform for self-promotion or promotion of products.
https://mementor.net
Socials
[ Virtual ]
With rapidly rising carbon emissions globally, it is the need of the hour to transition to clean energy sources – such as wind, solar etc. However, renewable energy sources like wind turbines are complex engineering systems that regularly suffer from operational inconsistencies and failures, leading to downtimes and energy production short of the full potential. AI can help support the operations & maintenance (O&M) of such energy systems, helping predict incipient failures and also suggesting maintenance actions to fix/avert faults. This can help bring down O&M costs as well as reduce downtimes and increase availability of the energy systems.
At present, there is very limited focus on leveraging AI in the renewables domain. This social will aim to emphasise the opportunities (e.g. fault prediction, suggesting O&M activities, power forecasting etc.) and challenges (e.g. data confidentiality in the industry, lack of historical failure data etc.) in applying AI for smoother transition to clean energy, with various avenues such as transfer learning and natural language generation to ensure trustworthy and reliable decision support. The social will focus on a short presentation from the organisers, followed by a panel discussion from invited experts on AI for renewable energy followed by open Q/A on …
[ Virtual ]
Optimization algorithms play an important role in training neural networks and their convergence. In this social, we shall discuss the efficiency of second order optimization and its acceleration using Nesterov's gradient.
[ Virtual ]
We look forward to meeting you at the conference! One event we are hosting that could be particularly helpful for job seekers is a webinar on How to Negotiate Industry Offers in AI. This is a brand new webinar with updated content if you've previously attended some of our events.
Some of the topics we discuss are:
"Lapsed" (aka. Former) Physicists are plentiful in the machine learning community. Inspired by Wine and Cheese seminars at many institutions, this BYOWC (Bring Your Own Wine and Cheese) event is an informal opportunity to connect with members of the community.
Hear how others made the transition between fields. Discuss how your physics training prepared you to switch fields or what synergies between physics and machine learning excite you the most. Share your favorite physics jokes your computer science colleagues don't get, and just meet other cool people. Open to everyone, not only physicists; you'll just have to tolerate our humor. Wine and Cheese encouraged, but not required."
ICLR selected paper discussion with Data Skeptic & PyData
"We invite everyone who is part of or interested in the ML research community in Korea. Participants introduce their own ML research presented in ICLR 2022. They also casually introduce papers that are found interesting among those presented in ICLR 2022 and other venues, and discuss those with other participants. Other potential discussion topics include (but are not limited to): Korean NLP, computer vision and datasets, ML for the post-COVID19 era, and career chances in both academia and industry in Korea. We welcome everyone from anywhere in the world. Note that we have had the same social events in ICLR 2020, 2021, NeurIPS 2020, and 2021 with active participation of more than 100 people.
Our social program is 3 hours long, including a 30 min keynote speech by Yejin Choi (Univ. of Washington), two 1 hour sessions with three tracks: industry tech. share, career mentoring for industrial research labs, and research discussions. As before, we will gather remotely through GatherTown.
We have 9 organizers from 3 different academy institutes (Tae-Hyun Oh, Gunhee Kim , and Seunghoon Hong ) and 6 industry corp. (Sanghyuk Chun , Woohyung Lim , Soonmin Bae , Saehoon Kim , Sungjoo Ha , and Junho …
Our presentations are most likely the highest impact activities we have as researchers. They are often quite dense. In those 10 minutes in your conference oral, you have the chance to show your work to a large audience for world-wide recognition. This is both incredibly stressful and difficult to do. The months of research that you've done, with all the ideas and all the results, have to be jam packed in a short time interval, and your audience is tired of the long conference and the information hoses they are drinking from. How do you make the most out of your presentation? How do you make sure that people understand your work, get excited by it, and remember you in the future?
In the first part of the session we will cover:
In the second part you are invited to bring your own presentations, which will be discussed in a small group. Don’t worry about getting …
Advanced economies are already using machine learning to solve problems like medical diagnosis, Improving Ecommerce Conversion Rates, traffic congestion, saving cows from bad drivers and improving healthcare, while developing nations lags conspicuously behind. Therefore it is important to discuss how machine learning could be used to address developing nation’s challenges by highlighting how some of the major challenges can be solved using certain machine learning techniques.
The main objective of the workshop will be to create awareness about the machine learning tools and its application in solving different problems in developing nations such as Ethiopia. Panelists are expected to brief how machine learning algorithms can be applied in health, agriculture, education, IcT, finance sectors.
Pretraining techniques and models largely advance research in language and vision. Several techniques are designed to better drive the model pretraining and fine-tuning in a more intelligent, robust and efficient manner. Meanwhile, with greater power of models come with greater concerns of their social impacts. Do larger models become more powerful consistently? Can larger models work reliably in larger-scale or even real-world applications? Developing models with fairness and reliability considerations therefore becomes increasingly significant.
This social event is launched in terms of collecting sparks of minds and opening discussions from findings to tips in better developing and fine-tuning large pretrained models, as well as the prospect of those models in social and scaling aspects.