Timezone: »
"Machine learning is a field without ongoing feuds, without heterogeneity of thought, without competing opinions, and without uncertainty over where the field is and where it is going. We all know this. We all use the same tools, have the same opinion about which libraries are the best, and what tools are best for tracking at train time. Yet, in this social event, we aim to find that rare soul in the AI/ML community with a primarily technical opinion that goes against the status quo, to give them a stage, and to curate engagement with an audience of NeurIPS members. Is symbolic reasoning dead? Who knows – but this discussion sure won’t be. Our goal here is to encourage a lively discussion, while ensuring that the speakers adhere to the NeurIPS Code of Conduct; in particular, by keeping the discussion respectful and professional.
The first half-hour of this social will be a reception, during which the organizers will pass around a sign-up for topics and for participants. We will ensure that the mic is accessible to everyone who wishes to participate, and we will aim for a diverse range of ideas, perspectives, and demographics. Then, we will have several rounds of open mic debates and response. The winners of each debate -- chosen by the audience -- will have eternal bragging rights."
Thu 4:00 p.m. - 6:00 p.m.
|
Social
|
🔗 |
Author Information
John Dickerson (Arthur AI & University of Maryland)
More from the Same Authors
-
2021 : Learning Revenue-Maximizing Auctions With Differentiable Matching »
Michael Curry · Uro Lyi · Tom Goldstein · John P Dickerson -
2021 : Learning Revenue-Maximizing Auctions With Differentiable Matching »
Michael Curry · Uro Lyi · Tom Goldstein · John P Dickerson -
2021 : An mHealth Intervention for African American and Hispanic Adults: Preliminary Results from a One-Year Field Test »
Christine Herlihy · John Dickerson -
2021 : An mHealth Intervention for African American and Hispanic Adults: Preliminary Results from a One-Year Field Test »
Christine Herlihy · John Dickerson -
2022 : A Deep Dive into Dataset Imbalance and Bias in Face Identification »
Valeriia Cherepanova · Steven Reich · Samuel Dooley · Hossein Souri · John Dickerson · Micah Goldblum · Tom Goldstein -
2022 : Tensions Between the Proxies of Human Values in AI »
Daniel Nissani · Teresa Datta · John Dickerson · Max Cembalest · Akash Khanna · Haley Massa -
2022 : Characterizing Anomalies with Explainable Classifiers »
Naveen Durvasula · Valentine d Hauteville · Keegan Hines · John Dickerson -
2022 : A Deep Dive into Dataset Imbalance and Bias in Face Identification »
Valeriia Cherepanova · Steven Reich · Samuel Dooley · Hossein Souri · John Dickerson · Micah Goldblum · Tom Goldstein -
2022 : On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition »
Samuel Dooley · Rhea Sukthanker · John Dickerson · Colin White · Frank Hutter · Micah Goldblum -
2022 : On the Importance of Architectures and Hyperparameters for Fairness in Face Recognition »
Samuel Dooley · Rhea Sukthanker · John Dickerson · Colin White · Frank Hutter · Micah Goldblum -
2022 : A Deep Dive into Dataset Imbalance and Bias in Face Identification »
Valeriia Cherepanova · Steven Reich · Samuel Dooley · Hossein Souri · John Dickerson · Micah Goldblum · Tom Goldstein -
2022 Workshop: Graph Learning for Industrial Applications: Finance, Crime Detection, Medicine and Social Media »
Manuela Veloso · John Dickerson · Senthil Kumar · Eren K. · Jian Tang · Jie Chen · Peter Henstock · Susan Tibbs · Ani Calinescu · Naftali Cohen · C. Bayan Bruss · Armineh Nourbakhsh -
2022 Poster: Robustness Disparities in Face Detection »
Samuel Dooley · George Z Wei · Tom Goldstein · John Dickerson -
2022 Poster: On the Generalizability and Predictability of Recommender Systems »
Duncan McElfresh · Sujay Khandagale · Jonathan Valverde · John Dickerson · Colin White -
2021 Poster: VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization »
Mucong Ding · Kezhi Kong · Jingling Li · Chen Zhu · John Dickerson · Furong Huang · Tom Goldstein -
2021 Poster: Fair Clustering Under a Bounded Cost »
Seyed Esmaeili · Brian Brubach · Aravind Srinivasan · John Dickerson -
2021 Poster: PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning »
Neehar Peri · Michael Curry · Samuel Dooley · John Dickerson -
2021 Poster: How does a Neural Network's Architecture Impact its Robustness to Noisy Labels? »
Jingling Li · Mozhi Zhang · Keyulu Xu · John Dickerson · Jimmy Ba -
2020 Workshop: Workshop on Dataset Curation and Security »
Nathalie Baracaldo · Yonatan Bisk · Avrim Blum · Michael Curry · John Dickerson · Micah Goldblum · Tom Goldstein · Bo Li · Avi Schwarzschild -
2020 Poster: Detection as Regression: Certified Object Detection with Median Smoothing »
Ping-yeh Chiang · Michael Curry · Ahmed Abdelkader · Aounon Kumar · John Dickerson · Tom Goldstein -
2020 Poster: Certifying Strategyproof Auction Networks »
Michael Curry · Ping-yeh Chiang · Tom Goldstein · John Dickerson -
2020 Poster: Improving Policy-Constrained Kidney Exchange via Pre-Screening »
Duncan McElfresh · Michael Curry · Tuomas Sandholm · John Dickerson -
2020 Poster: Probabilistic Fair Clustering »
Seyed Esmaeili · Brian Brubach · Leonidas Tsepenekas · John Dickerson -
2019 Poster: Making the Cut: A Bandit-based Approach to Tiered Interviewing »
Candice Schumann · Zhi Lang · Jeffrey Foster · John Dickerson -
2019 Poster: Adversarial training for free! »
Ali Shafahi · Mahyar Najibi · Mohammad Amin Ghiasi · Zheng Xu · John Dickerson · Christoph Studer · Larry Davis · Gavin Taylor · Tom Goldstein -
2015 : Uncertainty in Dynamic Matching »
John P Dickerson