Sujay Nagaraj
@snagaraj.bsky.social
MD/PhD student | University of Toronto | Machine Learning for Health
Reposted by Sujay Nagaraj
Denied a loan, an interview, or an insurance claim by machine learning models? You may be entitled to a list of reasons.
In our latest w @anniewernerfelt.bsky.social @berkustun.bsky.social @friedler.net, we show how existing explanation frameworks fail and present an alternative for recourse
In our latest w @anniewernerfelt.bsky.social @berkustun.bsky.social @friedler.net, we show how existing explanation frameworks fail and present an alternative for recourse
April 24, 2025 at 6:19 AM
Denied a loan, an interview, or an insurance claim by machine learning models? You may be entitled to a list of reasons.
In our latest w @anniewernerfelt.bsky.social @berkustun.bsky.social @friedler.net, we show how existing explanation frameworks fail and present an alternative for recourse
In our latest w @anniewernerfelt.bsky.social @berkustun.bsky.social @friedler.net, we show how existing explanation frameworks fail and present an alternative for recourse
Many ML models predict labels that don’t reflect what we care about, e.g.:
– Diagnoses from unreliable tests
– Outcomes from noisy electronic health records
In a new paper w/@berkustun, we study how this subjects individuals to a lottery of mistakes.
Paper: bit.ly/3Y673uZ
🧵👇
– Diagnoses from unreliable tests
– Outcomes from noisy electronic health records
In a new paper w/@berkustun, we study how this subjects individuals to a lottery of mistakes.
Paper: bit.ly/3Y673uZ
🧵👇
April 19, 2025 at 11:04 PM
Many ML models predict labels that don’t reflect what we care about, e.g.:
– Diagnoses from unreliable tests
– Outcomes from noisy electronic health records
In a new paper w/@berkustun, we study how this subjects individuals to a lottery of mistakes.
Paper: bit.ly/3Y673uZ
🧵👇
– Diagnoses from unreliable tests
– Outcomes from noisy electronic health records
In a new paper w/@berkustun, we study how this subjects individuals to a lottery of mistakes.
Paper: bit.ly/3Y673uZ
🧵👇
🚨 Excited to announce a new paper accepted at #ICLR2025 in Singapore!
“Learning Under Temporal Label Noise”
We tackle a new challenge in time series ML: label noise that changes over time 🧵👇
arxiv.org/abs/2402.04398
“Learning Under Temporal Label Noise”
We tackle a new challenge in time series ML: label noise that changes over time 🧵👇
arxiv.org/abs/2402.04398
Learning under Temporal Label Noise
Many time series classification tasks, where labels vary over time, are affected by label noise that also varies over time. Such noise can cause label quality to improve, worsen, or periodically chang...
arxiv.org
April 13, 2025 at 5:40 PM
🚨 Excited to announce a new paper accepted at #ICLR2025 in Singapore!
“Learning Under Temporal Label Noise”
We tackle a new challenge in time series ML: label noise that changes over time 🧵👇
arxiv.org/abs/2402.04398
“Learning Under Temporal Label Noise”
We tackle a new challenge in time series ML: label noise that changes over time 🧵👇
arxiv.org/abs/2402.04398