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Aishwarya Thiruvengadam
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Shashank Shrivastava
Shashidhar G
Shashin Halalingaiah
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Sheera Shamsu
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Shouvick Mondal
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Simran Kumari
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Sonam Gupta
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Srinivasa Desikan K E
Stephen L
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Sudha S
Sudhakar M
Sudhanshu Srivastava
Sugandha Tiwari
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Suman Banerjee
Sumanth Doddapaneni
Sumathi S
Suresh Kumar
Sutanay Bhattacharjee
Swarnava Ray
Syedghouse N
T Anand
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Utsav Dey
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Veera Venkata Narayana Dogiparthy
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Vikash Kumar
Vikram Singh
Vimala S
Vinay Kumar Verma
Vinod G
Vipin N S
Vishal S
Vishwajit Kumar Vishnu
Yadav Mahesh Lorik
Yajnesh Prasad Mohanty
Yamini Shankar
Yash Hareshkumar Madhani
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A Anunaya
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Aakarsh Darla
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Abhirup Majumder
Abhishek Bamniya
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Abul Kalam Azad Shaik
Adepu Vaishnavi
Adharsh V
Aditya C R
Aditya Jain
Aditya Kumar
Aditya Pravin Palwe
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Akhil Gupta
Akshat Gupta
Akshat Soni
Akshay M Potey
Alan D Andoor
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Aman Agarwal
Amar Kumar Sharma
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Aniket Keshri
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Chinmay Anil Pranjale
Chittabattula Sai Srikar Koushik
Daksh Sehra
Dasari Himakar Sai
Debasmita Mandal
Debendra Kumar Pal
Dev Tushar Mehta
Dharmasoth Sushanth
Dhruv Hemant Aggarwal
Dinesh Kumar S
Dinesh Naik Katravath
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Dixit Soham Vijay
Doddam Reddy Sasi Kumar Reddy
Drone Dangwal
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Dushyant Singh
Enna Sai Teja
Enukollu Naveen Koushik Reddy
Falgun Dnyanendra Meshram
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Ganesh T
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Godala Sthitha Pragna
Gokulakrishnan R
Golla Sai Harshith
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Joel Raj Kukkamalla
Juhi Arvindbhai Zanje
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K V Vikram
Kadiyam Veera Phani Sai Teja
Kakunuri Shashank Reddy
Kalipindi Prem Sagar
Kambhampati Gireesh
Kammara Guru Sai Kiran
Kanakamedala Vibhav Chowdary
Karan Agrawal
Karthik K
Katikela Puneeth Kumar
Katta Phalgun
Katte Pranjal Nandkumar
Kattupalli Bloomy
Kilaparthi Vishnu Vardhan
Kiran Jagdish Vasave
Kishore Kumar E
Kisulva Amarlal Vignesh
Kosireddy Sampath Kumar
Kothamaddi Venkata Pramodh Kumar
Kothapalli Sathvik Joel
Krish Johnson
Krishna Prasath D
Kritang Kothari
Kumar Kshitiz Singh
Kumaresan T M
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Kushagra Jain
Kushal Verma
L Akhil Siddhartha Rahul
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Limdiwala Dhaval Jayeshkumar
Lokesh Talamala
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Mohammed Abdul Muqeeth
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Yash Bhatia
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Area :
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Reinforcement Learning
Kernel Methods
Artifical Neural Networks
Deep Learning
Robot Learning
Natural Language Processing
Planning
Knowledge Representation
Memory Based Reasoning
Memory Models
Speech Synthesis and Recognition
Music Information Retrieval
Music Processing
Kernel Methods
Content based Information Retrieval
Handwritten Character Recognition
Visualization and Perception
Computer Graphics
Multi-camera Vision Systems
Human Detection and Tracking
Image Reconstruction
Soft Computing
Digital Video Processing
Memory System Design
Network-on-chip architectures
Cache Design in Multicore
Software Aspects
Design Automation
Digital VLSI
Formal Design Verification
Wireless Networks
Wireless Sensor Networks
Network Traffic Analysis and Modeling
Performance Evaluation
Optical Networks
Adhoc Wireless Networks
Program Analysis
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Fault Localization
Auto Parallelization & High Performance Compilers
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Cloud Computing
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Anonymous Remote Computation and Communication
Object Oriented Programming
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Smooth Analysis of Algorithms
Algebra and Computation
Circuit Complexity Theory
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Communication Complexity
Pseudorandomness
Boolean Function Analysis
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Inapproximability
Secure Multiparty Computation
Secret Sharing Schemes
Cryptography Protocols
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Indexing Semi-structured Data
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Text Summarization Systems
Ontologies
Semantic Web
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Implementations on GPUs
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Mouse Brain Architecture
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Systems Biology
Bioinformatics
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Operating System Security
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Network System Security
Structural Graph Theory
Enumerative Combinatorics
Combinatorial Optimization
Applications of Logic in Computer Science
Lab:
All
AIDB Lab
ACT Lab
PACE Lab
TCS Lab
Vision Lab
HPCN Lab
Networks Lab
ASHD Lab
DOS Lab
SV Lab
VP Lab
IIL Lab
SMV Lab
VLSI Lab
CASL Lab
MALT
CCD
RAnG
BIRDS
ToC
RL
SPACE
SENSE
AI4B
DAWNLAB
CCBR-EEG
RePReL: a unified framework for integrating relational planning and reinforcement learning for effective abstraction in discrete and continuous domains.
Hybrid Deep RePReL: Integrating Relational Planning and Reinforcement Learning for Information Fusion.
Harsha Kokel ,
Nikhilesh Prabhakar ,
Balaraman Ravindran ,
Erik Blasch ,
Prasad Tadepalli ,
Sriraam Natarajan
Appeared in
25th International Conference on Information Fusion, FUSION 2022, Linkping, Sweden, July 4-7, 2022 (FUSION 2022) ,
pp.1-8, Jul 2022.
RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction.
Harsha Kokel ,
Arjun Manoharan ,
Sriraam Natarajan ,
Balaraman Ravindran ,
Prasad Tadepalli
Appeared in
Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, ICASP 2021, Guangzhou, China (virtual), August 2-13, 2021 (ICASP 2021) ,
pp.533-541, Aug 2021.
Relational Boosted Bandits.
Ashutosh Kakadiya ,
Sriraam Natarajan ,
Balaraman Ravindran
Appeared in
Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021 ,
pp.12123-12130, Feb 2021.
Integrating Human Instructions and Reinforcement Learners: An SRL Approach.
Pradyot Korupolu V. N. ,
S. S. Manimaran ,
Balaraman Ravindran ,
Sriraam Natarajan
Appeared in
2nd International Workshop on Statistical Relational AI (StaRAI-12), held at the Uncertainty in Artificial Intelligence Conference (UAI 2012), Catalina Island, CA, USA, August 18, 2012 ,
Aug 2012.
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