Search Results - "Mukherjee, Debarghya"

Thyroid Function Test in Preterm Neonates: Normative Data by Mukherjee, Debarghya, Mukhopadhyay, Pradip, Saha, Bijan, Sen, Sangita, Ghosh, Sujoy

“…Initial surge of thyroid-stimulating hormone (TSH) in neonates increases free and total triiodothyronine (T3) and tetraiodothyronine (T4) in 24-36 hours…”
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Expression of GATA3, p63, E-cadherin and Her2Neu Immunohistochemical Stains in Urothelial Carcinoma and their Relationship with Histological Grading and Prognosis- A Cross-sectional Study by Mukherjee, Debarghya, Dey, Soumya, Chatterjee, Souvik, Mondal, Madhumita, Singh, Deepali, Sinha, Mamata Guha Mallick

“…Introduction: Urinary bladder cancer is the 10th most common cancer worldwide. Cystoscopy and biopsy/Transurethral Resection of Bladder Tumour (TURBT) are the…”
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Optimal linear discriminators for the discrete choice model in growing dimensions by Mukherjee, Debarghya, Banerjee, Moulinath, Ritov, Ya’acov

“…Manski's celebrated maximum score estimator for the discrete choice model, which is an optimal linear discriminator, has been the focus of much investigation…”
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Analysis of High Dimensional Statistical Models with Discontinuity by Mukherjee, Debarghya

“…This dissertation focuses on analyzing certain statistical models with roots in fields like economics, psychometry, etc. that can be put under the umbrella of…”
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Asymptotic normality of a change plane estimator in fixed dimension with near-optimal rate by Mukherjee, Debarghya, Banerjee, Moulinath, Mukherjee, Debasri, Ritov, Ya’acov

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On robust learning in the canonical change point problem under heavy tailed errors in finite and growing dimensions by Mukherjee, Debarghya, Banerjee, Moulinath, Ritov, Ya’acov

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Minimax Optimal rates of convergence in the shuffled regression, unlinked regression, and deconvolution under vanishing noise by Durot, Cecile, Mukherjee, Debarghya

“…Shuffled regression and unlinked regression represent intriguing challenges that have garnered considerable attention in many fields, including but not limited…”
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Trade-off Between Dependence and Complexity for Nonparametric Learning -- an Empirical Process Approach by Deb, Nabarun, Mukherjee, Debarghya

“…Empirical process theory for i.i.d. observations has emerged as a ubiquitous tool for understanding the generalization properties of various statistical…”
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On the estimation rate of Bayesian PINN for inverse problems by Sun, Yi, Mukherjee, Debarghya, Atchade, Yves

“…Solving partial differential equations (PDEs) and their inverse problems using Physics-informed neural networks (PINNs) is a rapidly growing approach in the…”
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Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift by Ge, Jiawei, Mukherjee, Debarghya, Fan, Jianqing

“…As machine learning models are increasingly deployed in dynamic environments, it becomes paramount to assess and quantify uncertainties associated with…”
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UTOPIA: Universally Trainable Optimal Prediction Intervals Aggregation by Fan, Jianqing, Ge, Jiawei, Mukherjee, Debarghya

“…Uncertainty quantification in prediction presents a compelling challenge with vast applications across various domains, including biomedical science,…”
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Deep Neural Networks for Nonparametric Interaction Models with Diverging Dimension by Bhattacharya, Sohom, Fan, Jianqing, Mukherjee, Debarghya

“…Deep neural networks have achieved tremendous success due to their representation power and adaptation to low-dimensional structures. Their potential for…”
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On robust learning in the canonical change point problem under heavy tailed errors in finite and growing dimensions by Mukherjee, Debarghya, Banerjee, Moulinath, Ritov, Ya'acov

“…This paper presents a number of new findings about the canonical change point estimation problem. The first part studies the estimation of a change point on…”
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Estimation of a score-explained non-randomized treatment effect in fixed and high dimensions by Mukherjee, Debarghya, Banerjee, Moulinath, Ritov, Ya'acov

“…Non-randomized treatment effect models are widely used for the assessment of treatment effects in various fields and in particular social science disciplines…”
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Transfer Learning Under High-Dimensional Graph Convolutional Regression Model for Node Classification by Chen, Jiachen, Huang, Danyang, Wang, Liyuan, Lunetta, Kathryn L, Mukherjee, Debarghya, Cheng, Huimin

“…Node classification is a fundamental task, but obtaining node classification labels can be challenging and expensive in many real-world scenarios. Transfer…”
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Predictor-corrector algorithms for stochastic optimization under gradual distribution shift by Maity, Subha, Mukherjee, Debarghya, Banerjee, Moulinath, Sun, Yuekai

“…Time-varying stochastic optimization problems frequently arise in machine learning practice (e.g. gradual domain shift, object tracking, strategic…”
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Domain Adaptation meets Individual Fairness. And they get along by Mukherjee, Debarghya, Petersen, Felix, Yurochkin, Mikhail, Sun, Yuekai

“…Many instances of algorithmic bias are caused by distributional shifts. For example, machine learning (ML) models often perform worse on demographic groups…”
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Post-processing for Individual Fairness by Petersen, Felix, Mukherjee, Debarghya, Sun, Yuekai, Yurochkin, Mikhail

“…Post-processing in algorithmic fairness is a versatile approach for correcting bias in ML systems that are already used in production. The main appeal of…”
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Outlier-Robust Optimal Transport by Mukherjee, Debarghya, Guha, Aritra, Solomon, Justin, Sun, Yuekai, Yurochkin, Mikhail

“…Optimal transport (OT) measures distances between distributions in a way that depends on the geometry of the sample space. In light of recent advances in…”
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Optimal Linear Discriminators For The Discrete Choice Model In Growing Dimensions by Mukherjee, Debarghya, Banerjee, Moulinath, Ritov, Ya'acov

“…Manski's celebrated maximum score estimator for the discrete choice model, which is an optimal linear discriminator, has been the focus of much investigation…”
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