no code implementations • 2 Apr 2023 • Ramtin Hosseini, Li Zhang, Bhanu Garg, Pengtao Xie
Our proposed framework involves three stages of learning, which are formulated as a three-level optimization problem: (i) learning to group problems into different subgroups; (ii) learning group-specific sub-models for problem-solving; and (iii) updating group assignments of training examples by minimizing the validation loss.
1 code implementation • 11 Nov 2021 • Bhanu Garg, Li Zhang, Pradyumna Sridhara, Ramtin Hosseini, Eric Xing, Pengtao Xie
We propose a novel machine learning method called Learning From Mistakes (LFM), wherein the learner improves its ability to learn by focusing more on the mistakes during revision.
no code implementations • 7 Dec 2019 • Bhanu Garg, Naresh Manwani
The real-world data is often susceptible to label noise, which might constrict the effectiveness of the existing state of the art algorithms for ordinal regression.