ALT Highlights – A Report on the First ALT Mentoring Workshop
Welcome to ALT Highlights, a series of blog posts spotlighting various happenings at the recent conference ALT 2021, including plenary talks, tutorials, trends in learning theory, and more! To reach a broad audience, the series will be disseminated as guest posts on different blogs in machine learning and theoretical computer science. This initiative is organized by the Learning Theory Alliance, and overseen by Gautam Kamath. All posts in ALT Highlights are indexed on the official Learning Theory Alliance blog.
This is the fifth post in the series, coverage of the first ALT Mentoring Workshop organized by the Learning Theory Alliance, written by Keziah Naggita and Sutanu Gayen.
1 Introduction
The Learning Theory Alliance (Let-All) is an online initiative aimed at developing a supportive learning theory community, founded by (1) Surbhi Goel, a postdoctoral researcher at Microsoft Research New York, (2) Nika Haghtalab, an assistant professor at UC Berkeley EECS, (3) and Ellen Vitercik, a Ph.D. Student at CMU; and advised by Peter Bartlett, Avrim Blum, Stefanie Jegelka, Po-Ling Loh, and Jenn Wortman Vaughan. The goal of the alliance is to ensure healthy community growth by fostering inclusive community engagement and encouraging active contributions from researchers at all stages of their careers. Let-All’s efforts towards realizing these goals include a series of ongoing and future activities, such as the first ALT mentoring workshop, coordinating the ALT Highlights blog series, and other upcoming community initiatives. This article reports on Let-All’s first Mentoring Workshop, which was affiliated with the 32nd International Conference on Algorithmic Learning Theory.
The workshop had two main sessions to cater to the time zone differences of the participants. These sessions had three main components: an academic program, which included how-to-talks, Ask Me Anythings (AMAs), and presentation dissections; a technical program, which included research talks; and a social program, which included discussion tables and other activities.
The workshop participants included students, researchers, and industry professionals, all at different levels of familiarity with learning theory. Because of the ongoing COVID-19 pandemic, the workshop was virtual. It was held on the online platforms Zoom and Gather town, a virtual interactive environment that mimics an in-person workshop setting. For accessibility, the workshop organizers opened up the workshop free of cost to all registered participants.
2 Program Highlights
2.1 Academic Program
To kick off the workshop, one of the organizers began with a welcome lecture: Surbhi in session one and Nika in session two. They read out the code of conduct and who to contact in case of issues, outlined the workshop’s purpose, and gave attendees demographic information. They explained how participants could navigate the workshop-themed Gather town workspace and then ended the introduction with encouragement for participants to mingle.
The How-to-Talks sessions covered writing papers, giving talks, and networking. In Session 1, Pravesh Kothari talked in great detail about the dos and don’ts of what to add in the abstract, overview, introduction, and appendix when advising participants on how to best structure research papers. He told attendees to always put effort into understanding their intended reader or talk audience. Pravesh encouraged attendees to consider the expertise and interests of the reader or listener to capture their attention since these highly determine the attention span and interest in the information presented to them. He strongly recommended attendees watch the Leadership Lab: The Craft of Writing Effectively by Larry McEnerney , Director of the University of Chicago Writing Program. In session 2 of the workshop, Rafael Frongillo, similar to Pravesh, discussed how to capture the intended audience when one writes a paper, reviews, and talks.
In the first networking session, Jacob Abernethy encouraged participants to seek out horizontal and vertical networking, for example, through collaborations, talks, and reach outs. He said that currently, in academia, Ph.D. admissions, faculty hiring, and tenure appointments are heavily risk-averse. Therefore, people seek out candidates based on their network. For this reason, it is crucial for students to network from early on in their careers. He gave great examples of how junior researchers can reach out and forge relationships with other researchers. For example, when you meet academics, faculty/postdocs at events, ask to give a talk at their lab. Jacob also candidly talked about his earlier failures at MIT and how they shaped his journey. He talked about luck and how John Langford, who was at Toyota Technological Institute at Chicago at the time, took a chance on him that forever changed his life. Jacob, therefore, advised academics to take chances on people as this would change the course of the field.
Jamie Morgenstern discussed different networking methods in the second How-to-talks session. She emphasized that for junior researchers, it’s important to attend conferences and to network with others, to advertise their research through talks, and to reach out to faculty for collaboration. To introduce oneself and capture the listener’s attention, Jamie said, for conferences, prepare to do so in two minutes, for social four minutes, bar 12 minutes, and faculty interview 25 minutes. Senior grad students may help introduce the juniors during lunch/poster sessions. Finally, when emailing faculty about research, she said one should avoid discussion about other people’s work and instead should stick to the recipient’s work – “showing deep understanding and possibly open questions which might lead to collaboration.”
In both workshop sessions, there were two parallel talk dissections, in which senior faculty members gave both positive and constructive feedback on talks junior researchers presented. In the first session, Bobby Kleinberg discussed Emily Diana‘s talk titled “Minimax and Lexicographically Fair Learning: Algorithms, Experiments, and Generalization”. He highlighted parts that were impressive, those that needed improvement, and gave general advice on structuring an audience-based presentation. When Bobby suggested including more diagrams than text, a few people made suggestions of free tools including tikz, matcha.io, PowerPoint, and draw.io. In parallel, Kamalika Chaudhuri dissected a talk on “Efficient, Noise-Tolerant, and Private Learning via Boosting” by Marco Carmosino. Two main takeaways of this talk dissection were the balance of technical and nontechnical content (e.g., explaining ideas with fun pictures, etc.) and having one main and clear idea as the talk’s takeaway.
In the second session, Mingda Qiao gave a talk titled: “Stronger Calibration Lower Bounds via Sidestepping” which Praneeth Netrapalli dissected. Praneeth remarked that theory folks often jump into the problem straight away without covering much background. In conferences, this might be fine due to time pressure and specific interests. However, in broader settings such as departmental seminars, he advised the speaker to allocate more time to introduce the problem lucidly and concisely. In parallel, Mary Wootters dissected a talk titled “List-Decodable Subspace Recovery: Dimension Independent Error in Polynomial Time” that Ainesh Bakshi presented.
In the first AMA session moderated by Aaditya Ramdas, Lester Mackey refreshingly answered several of the attendees’ well-curated questions about what makes strong collaborations, how to get into grad school, and whether or not he ever felt like quitting his Ph.D., among others. He encouraged students to take classes with professors they are interested in as it makes it easy to ask for a mentorship opportunity. Lester talked about collaborations and imposter syndrome and encouraged attendees to look on the brighter side of things, to remember that we all are working towards one big goal, creating positive changes in the world. Therefore if someone discovers a result before us, we should applaud them, collaborate if possible, and move onto new problems. He said he did not necessarily plan to do a Ph.D. but got into it towards the end of his undergraduate degree due to an internship that made him fall in love with doing research.
In the evening, there was an AMA session with Shafi Goldwasser moderated by Nika. Shafi gave thoughtful and candid answers to attendees’ captivating questions about research, life in academia, collaborations, among others. Shafi told attendees that healthy competition, trust, and overlap of research interest, is crucial for successful research in the early stage of the career. She also asserted that fundamental science is always impactful. She mentioned that the high points of her career were working on problems she was curious about: cryptography, pseudo-randomness, and zero-knowledge proofs. Finally, when asked about what advice she wished she had during the early stage of her career, interestingly Shafi replied: “having good colleagues, good friends at work, very important, most important – having a listening, promoting and supportive cohort of friends rather than an individualistic path as a scholar is priceless.”
2.2 Technical Program
Two research talks happened in the first session. First, Po-Ling Loh gave a talk titled “Mean estimation for entangled single-sample distributions.” Then Vatsal Sharan talked about “Sample Amplification: Increasing Dataset Size even when Learning is Impossible”.
Similarly in the second session, Nadav Cohen gave the first talk about tensor and matrix completion problems and the importance of understanding the theory behind deep learning from theoretical and practical perspectives. After, Zhiyi Huang gave a talk titled “Setting the Sample Complexity of Single-parameter Revenue Maximization.”
2.3 Social Program
In both sessions, during the social hours, Sumegha Garg, Suriya Gunasekar, and Thodoris Lykouris organized the table topics to help attendees meet and interact with senior researchers and professors on different topics. The table topics included the following; starting on ML research, research agendas, ML+X: multidisciplinary research, advisor-advisee relationships, collaborators, communicating research and networking, beyond your institution: internships and research visits, planning after grad school: academia versus industry, Grad school applications, Work ethics, and Open research discussion.
The table topics were chaired by; Jacob Abernethy, Shivani Agarwal, Eric Balkanski, Peter Bartlett, Avrim Blum, Sébastien Bubeck, Kamalika Chaudhuri, Nadav Cohen, Sumegha Garg, Surbhi Goel, Suriya Gunasekar, Nika Haghtalab, Daniel Hsu, Prateek Jain, Mike Jordan, Sham Kakade, Adam Kalai, Pravesh Kothari, Akshay Krishnamurthy, Jerry Li, Po-Ling Loh, Thodoris Lykouris, Yishay Mansour, Pasin Manurangsi, Vidya Muthukumar, Praneeth Netrapalli, Wen Sun, Bo Waggoner, Manolis Zampetakis, and Cyril Zhang.
Lastly, at the end of the two general research talks in sessions one and two of the workshop, attendees assembled on Gather town to close the workshop. The social event included 1:1 social interactions with other attendees, an attempt at forging relationships, and activities like dancing.
3 Attendance Statistics, Testimonials and Feedback
3.1 Participants Statistics
ALT mentoring workshop welcomed talented academics, researchers, and professionals from a wide array of backgrounds. Of the 438 registered to attend the workshop, 197 were new to the learning theory community, 37 attended at least one ALT/COLT conference in the past, and 146 hadn’t attended ALT/COLT but had attended machine learning conferences (STOC, NeurIPS, etc.) as shown in Figure 1.
The workshop participants came from different parts of the world, were of different genders, races, and seniority levels. We use Figures 2, 3b, 4a, and 4b to highlight this demographic information about the participants. Some participants chose session one, and others chose session two, a choice driven by their schedules and time zones. The attendance composition is as shown in figure 3a.
3.2 Testimonials and Feedback
In this section, we give a recount of testimonials from participants who we interviewed after the workshop. We also highlight some of the common themes in feedback from participants.
In general, participants loved the content delivered in the sessions. They said it was informative, intuitive, and rare to find. Several participants loved interacting with peers and senior members and wished they had more time and activities to do it. The How-to-talks session (focused on networking skills, structuring papers, talks, and reviews) was the most popular session among attendees. 76.7% of the survey respondents said the session helped them gain new technical skills or hone existing skills, see opportunities in academia and how to use them, and see barriers in academia and ways to overcome them. Figure 5 highlights attendees’ ratings of the skills acquired from the workshop.
Below is a recount of the workshop experiences of the interviewed attendees.
“My highlight was the How-to-Talks since they provided a lot of more personal information/inputs that you cannot easily find online and which was very valuable. The event helped me to remember and reflect upon which qualities are crucial to becoming a good researcher. I even made a list in a place that I see every day to keep them in mind.” – Michael Aerni, MSc student at ETH Zurich.
“The workshop highlights for me were the How-to-talks, the AMA session with Lester, and the social tables. The How-to-talks were extremely valuable as they discussed topics such as structuring papers and networking in the community. These are subtle aspects that are not often explicitly talked about in the community. I, therefore, learned a lot from them. The AMA session was refreshingly honest and open. Finally, the social tables were also great as I got to meet and talk to some well-established senior community members like Sebastien Bubeck, Shivani Agarwal, and Akshay Krishnamurthy.” – Tanmay Gautam, a second-year Ph.D. student at UC Berkeley.
“It was awesome to have Lester Mackey answer my questions, indubitably. I learned about staying true to the research questions I genuinely believe in regardless of external opinions and rewards. As an NYU AI School organizer, I can appreciate how much effort went into organizing the workshop. The organizers did a stellar job! I think a version of the same event again would be perfect.” – Swapneel Mehta, a Data Science Ph.D. student at New York University.
“My highlights were getting to talk with senior members of the community. These opportunities rarely come by for someone who lives in a foreign country. For a timid person like myself, I am also thankful for the senior members for helping me (and other participants) breaking the ice and easing us into the conversations. Thanks to this event, I am now more confident in engaging with other researchers.”- Donlapark Ponnoprat, a Statistics lecturer at Chiang Mai University.
“My main highlights were Dr. Goldwasser’s session with Dr. Haghtalab and the socials. In the socials, I was able to ask professors and senior researchers for advice on varied topics based on the tables. Insights from Dr. Cohen’s lecture on tensor rank and implicit regularisation gave me several pointers to ideas in the literature that I was not aware of as a junior researcher from a slightly different AI specialty. These ideas might be beneficial for my research in the long term.
I send a sincere thank you to all the organizers. The mentorship workshop was a great event, and it models concrete actions, what it means to foster a welcoming community. It is clear how kind and dedicated folks are here as some researchers even stayed beyond midnight in their time zones to answer questions that attendees had. If an event like this happens again, I am most definitely signing up to come.” – Esra’a Saleh, a Masters in Computer Science student at the University of Alberta, affiliated with AMII and RLAI.
“My main takeaway from the event was an inside look at academia. As an undergrad, my only experience in academia has been the little experience I have with my advisory professors. While this is an invaluable experience, this event was nice as it was one of the very few that cater to students, including undergrads, with the intent of bringing them into the academia fold. Getting to know new people and talking to them was extremely interesting, especially during lockdown when connecting with others is a much more valuable commodity.” – Shrey Shah, a penultimate year undergraduate student at the University of Wisconsin-Madison.
Several participants enjoyed the workshop sessions and hoped that Let-All holds more similar themed workshops in conferences. Attendees suggested ways for attendees to interact more with each other. Some of the suggestions included the following: ‘beginner-friendly open problems sessions where attendees can collaborate’ – Esra’a Saleh, ‘an icebreaker session at the beginning that encourages attendees to mingle’ – Michael Aerni, and ‘a poster session for participants to present their work’ – Shrey Shah.
4 Conclusion
The ALT mentorship workshop organized by the Learning Theory Alliance brought together many academics and researchers. It was, and we hope it continues to be, an opportunity for the budding researchers to learn about research and meta-research, forge collaborations, and be inspired. Kudos to the organizers and the Alliance in general for dreaming such a positive vision and then striving to make it a great success!
Thanks to Gautam Kamath, Margalit Glasgow, Surbhi Goel, Nika Haghtalab and Ellen Vitercik for helpful conversations and comments.
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