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Sanjay Krishnan

7 accepted papers

2019

Band-limited Training and Inference for Convolutional Neural Networks

ICML 2019oral

The convolutional layers are core building blocks of neural network architectures. In general, a convolutional filter applies to the entire frequency spectrum of the input data. We explore artificially constraining the frequency spectra of these filters and data, called band-limiting, during trainin…

Cited by 61SourcePDFScholar
2018

Fast and Reliable Autonomous Surgical Debridement with Cable-Driven Robots Using a Two-Phase Calibration Procedure

ICRA 2018poster

Automating precision subtasks such as debridement (removing dead or diseased tissue fragments) with Robotic Surgical Assistants (RSAs) such as the da Vinci Research Kit (dVRK) is challenging due to inherent nOnlinearities in cable-driven systems. We propose and evaluate a novel two-phase coarse-to-f…

Cited by 82SourceScholar
2018

Parametrized Hierarchical Procedures for Neural Programming

ICLR 2018poster

Neural programs are highly accurate and structured policies that perform algorithmic tasks by controlling the behavior of a computation mechanism. Despite the potential to increase the interpretability and the compositionality of the behavior of artificial agents, it remains difficult to learn from…

Cited by 35SourcePDFScholar
2017

Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations

ICRA 2017poster

Motivated by recent advances in Deep Learning for robot control, this paper considers two learning algorithms in terms of how they acquire demonstrations from fallible human supervisors. Human-Centric (HC) sampling is a standard supervised learning algorithm, where a human supervisor demonstrates th…

Cited by 89SourceScholar
2017

DDCO: Discovery of Deep Continuous Options for Robot Learning from Demonstrations

CoRL 2017

An option is a short-term skill consisting of a control policy for a specified region of the state space, and a termination condition recognizing leaving that region. In prior work, we proposed an algorithm called Deep Discovery of Options (DDO) to discover options to accelerate reinforcement learni

Cited by 0SourcePDFScholar
2017

Multilateral surgical pattern cutting in 2D orthotropic gauze with deep reinforcement learning policies for tensioning

ICRA 2017poster

In the Fundamentals of Laparoscopic Surgery (FLS) standard medical training regimen, the Pattern Cutting task requires residents to demonstrate proficiency by maneuvering two tools, surgical scissors and tissue gripper, to accurately cut a circular pattern on surgical gauze suspended at the corners.…

Cited by 178SourceScholar
2016

TSC-DL: Unsupervised trajectory segmentation of multi-modal surgical demonstrations with Deep Learning

ICRA 2016

The growth of robot-assisted minimally invasive surgery has led to sizable datasets of fixed-camera video and kinematic recordings of surgical subtasks. Segmentation of these trajectories into locally-similar contiguous sections can facilitate learning from demonstrations, skill assessment, and salv

Cited by 77SourcecodeScholar