Person: Satinder P. Singh

DBLP: Singh:Satinder_P=

Contributed to:

2013

2010

2008

2007

2006

2005

2004

2003

2000

1998

1994

1992

1991

Wrote 19 papers:

HCI-AMTE-2013-FearyBCHLSS #design #evaluation #interface #safety

Linking Context to Evaluation in the Design of Safety Critical Interfaces (MF, DB, XC, AH, RLL, LS, SPS), pp. 193–202.

ICML-2010-SorgSL #bound

Internal Rewards Mitigate Agent Boundedness (JS, SPS, RLL), pp. 1007–1014.

ICML-2008-WingateS #exponential #learning #predict #product line

Efficiently learning linear-linear exponential family predictive representations of state (DW, SPS), pp. 1176–1183.

SIGMOD-2007-LiCYSJ #adaptation #interface #named #natural language #query #xml

DaNaLIX: a domain-adaptive natural language interface for querying XML (YL, IC, HY, SPS, HVJ), pp. 1165–1168.

ICML-2006-RudaryS #modelling #predict #probability

Predictive linear-Gaussian models of controlled stochastic dynamical systems (MRR, SPS), pp. 777–784.

ICML-2006-WingateS #kernel #linear #modelling #predict #probability

Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems (DW, SPS), pp. 1017–1024.

ICML-2006-WolfeS #predict

Predictive state representations with options (BW, SPS), pp. 1025–1032.

ICML-2005-WolfeJS #learning #predict

Learning predictive state representations in dynamical systems without reset (BW, MRJ, SPS), pp. 980–987.

ICML-2004-JamesS #learning #predict

Learning and discovery of predictive state representations in dynamical systems with reset (MRJ, SPS).

ICML-2004-RudarySP #adaptation #constraints #learning #reasoning

Adaptive cognitive orthotics: combining reinforcement learning and constraint-based temporal reasoning (MRR, SPS, MEP).

ICML-2003-SinghLJPS #learning #predict

Learning Predictive State Representations (SPS, MLL, NKJ, DP, PS), pp. 712–719.

ICML-2000-MyersKSW #approach #topic

A Boosting Approach to Topic Spotting on Subdialogues (KM, MJK, SPS, MAW), pp. 655–662.

ICML-2000-PrecupSS #evaluation #policy

Eligibility Traces for Off-Policy Policy Evaluation (DP, RSS, SPS), pp. 759–766.

ICML-1998-KearnsS #learning

Near-Optimal Reinforcement Learning in Polynominal Time (MJK, SPS), pp. 260–268.

ICML-1998-LochS #markov #policy #process #using

Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes (JL, SPS), pp. 323–331.

ICML-1998-SuttonPS #learning

Intra-Option Learning about Temporally Abstract Actions (RSS, DP, SPS), pp. 556–564.

ICML-1994-SinghJJ #learning #markov #process

Learning Without State-Estimation in Partially Observable Markovian Decision Processes (SPS, TSJ, MIJ), pp. 284–292.

ML-1992-Singh #algorithm #learning #modelling #scalability

Scaling Reinforcement Learning Algorithms by Learning Variable Temporal Resolution Models (SPS), pp. 406–415.

ML-1991-Singh #composition #learning

Transfer of Learning Across Compositions of Sequentail Tasks (SPS), pp. 348–352.