Virtual Presentations and Poster Session

Due to the virtual format of this year’s NewInML Workshop, we are hosting our Q&A through the NewInML Slack. This will allow for authors and attendees in different timezones to participate in Q&A. You can find the Slack signup link in the NewInML schedule on the main conference site. There is one channel for each paper, named “author_X”, where X is the last name of the first author of each paper (e.g. author_agrawal).

Oral Presentations Links
Investigating Learning in Deep Neural Networks using Layer-Wise Weight Change
Ayush Manish Agrawal, Atharva Tendle, Harshvardhan Sikka, Sahib Singh, Amr Kayid
Video
Poster
Adversarial Training with a Surrogate
Keane Lucas, Alec Jasen, Lujo Bauer
Video
Poster
Leveraging Kinematic Space for Deep Representation Learning
Adarsh Jamadandi and Uma Mudenagudi
Video
Poster
TinySpeech: Attention Condensers for Deep Speech Recognition Neural Networks on Edge Devices
Alexander Wong, Mahmoud Famouri, Maya Pavlova, Siddharth Surana
Video
Poster


Poster Session Links
Deep Learning Towards Efficient Malaria Dataset Creation
Martha Shaka, Frederick Apina, Nyamos Waigama, Halidi Maneno, Said H Said, Emilian Ngatunga, Said Mmaka, Simon Chaula, Imani Sulutya, and Merikiadi Mashaka
Poster
UmlsBERT: Clinical Domain Knowledge Augmentation of Contextual Embeddings Using the Unified Medical Language System Metathesaurus
George Michalopoulos, Yuanxin Wang, Hussam Kaka, Helen Chen, Alex Wong
Poster
How to Control the Error Rates of Binary Classifiers
Miloš Simić
Poster
Inter-layer Information Similarity Assessment of Deep Neural Networks Via Topological Similarity and Persistence Analysis of Data Neighbour Dynamics
Andrew Hryniowski and Alexander Wong
Poster
Large-scale Open Dataset, Pipeline, and Benchmark for Bandit Algorithms
Yuta Saito, Shunsuke Aihara, Megumi Matsutani, Yusuke Narita
Poster
Vulnerability Under Adversarial Machine Learning: Bias or Variance?
Hossein Aboutalebi, Mohammad Javad Shafiee, Michelle Karg, Christian Scharfenberger, Alexander Wong
Poster
Identifying and Characterising Response in Clinical Trials: Development and Validation of a Machine Learning Approach in Colorectal Cancer
Adam Marcus and Paul Agapow
Poster