Her Nanotechnology study frequently draws parallels with other fields, such as Thin film and Atomic layer deposition. Her Thin film study typically links adjacent topics like Nanotechnology. Among her Pure mathematics studies, you can observe a synthesis of other disciplines of science such as Quantum mechanics and Combinatorics. In her research, she performs multidisciplinary study on Quantum mechanics and Pure mathematics. She integrates Combinatorics with Discrete mathematics in her study. Aarti Singh brings together Discrete mathematics and Statistics to produce work in her papers. Aarti Singh integrates Statistics with Algorithm in her research. Many of her studies involve connections with topics such as Parameterized complexity and Algorithm. With her scientific publications, her incorporates both Artificial intelligence and Artificial neural network.
Aarti Singh applies her multidisciplinary studies on Artificial intelligence and Algorithm in her research. She undertakes multidisciplinary investigations into Algorithm and Artificial intelligence in her work. Aarti Singh integrates many fields, such as Statistics and Mathematical optimization, in her works. In her research, she undertakes multidisciplinary study on Mathematical optimization and Statistics.
In her study, Minimax is inextricably linked to Mathematical optimization, which falls within the broad field of Minification. Minimax and Mathematical optimization are frequently intertwined in her study. Her work in Test (biology) addresses issues such as Paleontology, which are connected to fields such as Context (archaeology). Her research links Paleontology with Context (archaeology). Cell biology and Microbiology are two areas of study in which Aarti Singh engages in interdisciplinary research. Her work blends Microbiology and Immunology studies together. Many of her studies on Immunology apply to Translocator protein as well. Her work in Translocator protein is not limited to one particular discipline; it also encompasses Neuroinflammation. She integrates many fields in her works, including Neuroinflammation and Inflammation.
Aarti Singh integrates Mitochondrion and Translocator protein in her research. Translocator protein is closely attributed to Inflammation in her study. She incorporates Inflammation and Apoptosis in her research. Aarti Singh performs multidisciplinary studies into Apoptosis and Mitochondrion in her work. Her Cell biology study frequently links to related topics such as Mediator. Aarti Singh carries out multidisciplinary research, doing studies in Mediator and Gene. Her Gene study frequently links to other fields, such as Retrograde signaling. As part of her studies on Retrograde signaling, she frequently links adjacent subjects like Biochemistry. Her Biochemistry study frequently draws connections between related disciplines such as Transcription factor.
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Gradient Descent Provably Optimizes Over-parameterized Neural Networks
Simon S. Du;Xiyu Zhai;Barnabas Poczos;Aarti Singh.
international conference on learning representations (2018)
Unlabeled data: Now it helps, now it doesn't
Aarti Singh;Robert Nowak;Xiaojin Zhu.
neural information processing systems (2008)
Decentralized compression and predistribution via randomized gossiping
Michael Rabbat;Jarvis Haupt;Aarti Singh;Robert Nowak.
information processing in sensor networks (2006)
Confidence sets for persistence diagrams
Brittany Therese Fasy;Fabrizio Lecci;Alessandro Rinaldo;Larry Wasserman.
Annals of Statistics (2014)
Data Poisoning Attacks on Factorization-Based Collaborative Filtering
Bo Li;Yining Wang;Aarti Singh;Yevgeniy Vorobeychik.
neural information processing systems (2016)
Gradient Descent Can Take Exponential Time to Escape Saddle Points
Simon S. Du;Chi Jin;Jason D. Lee;Michael I. Jordan.
neural information processing systems (2017)
Multi-Manifold Semi-Supervised Learning
Andrew B. Goldberg;Xiaojin Zhu;Aarti Singh;Zhiting Xu.
international conference on artificial intelligence and statistics (2009)
Gradient Descent Learns One-hidden-layer CNN: Don’t be Afraid of Spurious Local Minima
Simon S. Du;Jason D. Lee;Yuandong Tian;Barnabas Poczos.
international conference on machine learning (2018)
Low-Rank Matrix and Tensor Completion via Adaptive Sampling
Akshay Krishnamurthy;Aarti Singh.
neural information processing systems (2013)
On the decreasing power of kernel and distance based nonparametric hypothesis tests in high dimensions
Aaditya Ramdas;Sashank J. Reddi;Barnabás Póczos;Aarti Singh.
national conference on artificial intelligence (2015)
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